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<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">Moderation (statistics)</span></span>
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<p>In <a href="Statistics" title="Statistics">statistics</a> and <a href="Regression_analysis" title="Regression analysis">regression analysis</a>, <b>moderation</b> (also known as <b>effect modification</b>) occurs when the relationship between two variables depends on a third variable. The third variable is referred to as the <b>moderator variable</b> (or <b>effect modifier</b>) or simply the <b>moderator</b> (or <b>modifier</b>).<sup id="cite_ref-cohen_1-0" class="reference"><a href="#cite_note-cohen-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> The effect of a moderating variable is characterized statistically as an <a href="Interaction_(statistics)" title="Interaction (statistics)"><b>interaction</b></a>;<sup id="cite_ref-cohen_1-1" class="reference"><a href="#cite_note-cohen-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> that is, a <a href="Categorical_variable" title="Categorical variable">categorical</a> (e.g., sex, ethnicity, class) or <a href="Level_of_measurement" title="Level of measurement">continuous</a> (e.g., age, level of reward) <a href="Variable_(mathematics)" title="Variable (mathematics)">variable</a> that is associated with the direction and/or magnitude of the relation between <a href="Dependent_and_independent_variables" title="Dependent and independent variables">dependent and independent variables</a>. Specifically within a <a href="Correlation" title="Correlation">correlational</a> analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variables, or the value of the slope of the dependent variable on the independent variable. In <a href="Analysis_of_variance" title="Analysis of variance">analysis of variance</a> (ANOVA) terms, a basic moderator effect can be represented as an <a href="Interaction_(statistics)" title="Interaction (statistics)">interaction</a> between a focal <a href="Statistical_independence" class="mw-redirect" title="Statistical independence">independent</a> variable and a factor that specifies the appropriate conditions for its operation.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup>
</p>
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<div class="mw-heading mw-heading2"><h2 id="Example">Example</h2></div>
<p>Moderation analysis in the <a href="Behavioral_sciences" class="mw-redirect" title="Behavioral sciences">behavioral sciences</a> involves the use of <a href="Linear_regression" title="Linear regression">linear multiple regression analysis</a> or <a href="Causal_modelling" class="mw-redirect" title="Causal modelling">causal modelling</a>.<sup id="cite_ref-cohen_1-2" class="reference"><a href="#cite_note-cohen-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> To quantify the effect of a moderating variable in multiple regression analyses, regressing <a href="Random_variable" title="Random variable">random variable</a> <i>Y</i> on <i>X</i>, an additional term is added to the model. This term is the interaction between <i>X</i> and the proposed moderating variable.<sup id="cite_ref-cohen_1-3" class="reference"><a href="#cite_note-cohen-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup>
</p><p>Thus, for a response <i>Y</i> and two variables: <i>x</i><sub>1</sub> and moderating variable <i>x</i><sub>2</sub>,:
</p>
<dl><dd><span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle Y=b_{0}+b_{1}x_{1}+b_{2}x_{2}+b_{3}(x_{1}\times x_{2})+\varepsilon \,}">
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<annotation encoding="application/x-tex">{\displaystyle Y=b_{0}+b_{1}x_{1}+b_{2}x_{2}+b_{3}(x_{1}\times x_{2})+\varepsilon \,}</annotation>
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</math></span><img src="./7a18c972d12c8d39eed85e403dea25c701294dce.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.838ex; width:40.096ex; height:2.843ex;" alt="{\displaystyle Y=b_{0}+b_{1}x_{1}+b_{2}x_{2}+b_{3}(x_{1}\times x_{2})+\varepsilon \,}" loading="lazy"></span></dd></dl>
<p>In this case, the role of <i>x</i><sub>2</sub> as a moderating variable is accomplished by evaluating <i>b</i><sub>3</sub>, the parameter estimate for the interaction term.<sup id="cite_ref-cohen_1-4" class="reference"><a href="#cite_note-cohen-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> See <a href="Linear_regression" title="Linear regression">linear regression</a> for discussion of statistical evaluation of parameter estimates in regression analyses.
</p>
<div class="mw-heading mw-heading2"><h2 id="Multicollinearity_in_moderated_regression">Multicollinearity in moderated regression</h2></div>
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</style><div role="note" class="hatnote navigation-not-searchable">Further information: <a href="Multicollinearity" title="Multicollinearity">Multicollinearity</a></div>
<p>In moderated regression analysis, a new <a href="Interaction_(statistics)" title="Interaction (statistics)">interaction</a> predictor (<span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle x_{1}x_{2}}">
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</p><p>Mean-centering (subtracting raw scores from the mean) may reduce multicollinearity, resulting in more interpretable regression coefficients.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> However, it does not affect the overall model fit.
</p>
<div class="mw-heading mw-heading2"><h2 id="Post-hoc_probing_of_interactions">Post-hoc probing of interactions</h2></div>
<p>Like simple main effect analysis in ANOVA, in post-hoc probing of interactions in regression, we are examining the simple slope of one independent variable at the specific values of the other independent variable. Below is an example of probing two-way interactions.
In what follows, the regression equation with two variables A and B and an interaction term A*B,
</p>
<dl><dd><span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}A*B+\varepsilon }">
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<p>will be considered.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup>
</p>
<div class="mw-heading mw-heading3"><h3 id="Two_categorical_independent_variables">Two categorical independent variables</h3></div>
<p>If both of the independent variables are categorical variables, we can analyze the results of the regression for one independent variable at a specific level of the other independent variable. For example, suppose that both A and B are single dummy coded (0,1) variables, and that A represents ethnicity (0 = European Americans, 1 = East Asians) and B represents the condition in the study (0 = control, 1 = experimental). Then the interaction effect shows whether the effect of condition on the dependent variable Y is different for European Americans and East Asians and whether the effect of ethnic status is different for the two conditions.
The coefficient of A shows the ethnicity effect on Y for the control condition, while the coefficient of B shows the effect of imposing the experimental condition for European American participants.
</p><p>To probe if there is any significant difference between European Americans and East Asians in the experimental condition, we can simply run the analysis with the condition variable reverse-coded (0 = experimental, 1 = control), so that the coefficient for ethnicity represents the ethnicity effect on Y in the experimental condition. In a similar vein, if we want to see whether the treatment has an effect for East Asian participants, we can reverse code the ethnicity variable (0 = East Asians, 1 = European Americans).
</p>
<div class="mw-heading mw-heading3"><h3 id="One_categorical_and_one_continuous_independent_variable">One categorical and one continuous independent variable</h3></div>
<p>If the first independent variable is a categorical variable (e.g. gender) and the second is a continuous variable (e.g. scores on the Satisfaction With Life Scale (SWLS)), then <i>b</i><sub>1</sub> represents the difference in the dependent variable between males and females when <a href="Life_satisfaction" title="Life satisfaction">life satisfaction</a> is zero. However, a zero score on the Satisfaction With Life Scale is meaningless as the range of the score is from 7 to 35. This is where centering comes in. If we subtract the mean of the SWLS score for the sample from each participant's score, the mean of the resulting centered SWLS score is zero. When the analysis is run again, <i>b</i><sub>1</sub> now represents the difference between males and females at the mean level of the SWLS score of the sample.
</p>
<p>Cohen et al. (2003) recommended using the following to probe the simple effect of gender on the dependent variable (<i>Y</i>) at three levels of the continuous independent variable: high (one standard deviation above the mean), moderate (at the mean), and low (one standard deviation below the mean).<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> If the scores of the continuous variable are not standardized, one can just calculate these three values by adding or subtracting one standard deviation of the original scores; if the scores of the continuous variable are standardized, one can calculate the three values as follows: high = the standardized score minus 1, moderate (mean = 0), low = the standardized score plus 1. Then one can explore the effects of gender on the dependent variable (<i>Y</i>) at high, moderate, and low levels of the SWLS score. As with two categorical independent variables, <i>b</i><sub>2</sub> represents the effect of the SWLS score on the dependent variable for females. By reverse coding the gender variable, one can get the effect of the SWLS score on the dependent variable for males.
</p>
<div class="mw-heading mw-heading4"><h4 id="Coding_in_moderated_regression">Coding in moderated regression</h4></div>
<p>When treating categorical variables such as ethnic groups and experimental treatments as independent variables in moderated regression, one needs to code the variables so that each code variable represents a specific setting of the categorical variable. There are three basic ways of coding: dummy-variable coding, contrast coding and effects coding. Below is an introduction to these coding systems.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup>
</p>
<p><b>Dummy coding</b> compares a reference group (one specific condition such as a control group in the experiment) with each of the other experimental groups. In this case, the intercept <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle b_{0}={\bar {Y}}_{\text{reference}}}">
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</p><p><b>Contrast coding</b> investigates a series of orthogonal contrasts (group comparisons). The intercept <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle b_{0}={\overline {{\bar {Y}}_{1\dots n}}}}">
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<annotation encoding="application/x-tex">{\displaystyle b_{A,B}={\bar {Y}}_{B}-{\bar {Y}}_{A}}</annotation>
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</math></span><img src="./2bab4a9068840943d50ba7e471e86b4d95e4eb42.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -1.005ex; width:16.597ex; height:3.176ex;" alt="{\displaystyle b_{A,B}={\bar {Y}}_{B}-{\bar {Y}}_{A}}" loading="lazy"></span> represents the difference between two groups. This coding system is appropriate when researchers have an a priori hypothesis concerning the specific differences among the group means.
</p><p><b>Effects coding</b> is used when there is no reference group or orthogonal contrasts. The intercept <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle b_{0}}">
<semantics>
<mrow class="MJX-TeXAtom-ORD">
<mstyle displaystyle="true" scriptlevel="0">
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<annotation encoding="application/x-tex">{\displaystyle b_{0}}</annotation>
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</math></span><img src="./9e425056f502ca07b103ffbf6ac4720e0f8a01f0.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:2.052ex; height:2.509ex;" alt="{\displaystyle b_{0}}" loading="lazy"></span> is the grand mean (the mean of all the conditions). The regression coefficient <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle b_{A}={\bar {Y}}_{A}-{\overline {{\bar {Y}}_{1\dots n}}}}">
<semantics>
<mrow class="MJX-TeXAtom-ORD">
<mstyle displaystyle="true" scriptlevel="0">
<msub>
<mi>b</mi>
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<mo>=</mo>
<msub>
<mrow class="MJX-TeXAtom-ORD">
<mrow class="MJX-TeXAtom-ORD">
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<mo stretchy="false">¯<!-- ¯ --></mo>
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<mi>A</mi>
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<mo stretchy="false">¯<!-- ¯ --></mo>
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<mn>1</mn>
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<mo accent="false">¯<!-- ¯ --></mo>
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<annotation encoding="application/x-tex">{\displaystyle b_{A}={\bar {Y}}_{A}-{\overline {{\bar {Y}}_{1\dots n}}}}</annotation>
</semantics>
</math></span><img src="./8bba6731e127b2b6cb5a5d2cd308e0ce773b8ae4.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:17.494ex; height:3.676ex;" alt="{\displaystyle b_{A}={\bar {Y}}_{A}-{\overline {{\bar {Y}}_{1\dots n}}}}" loading="lazy"></span> is the difference between one group mean and the mean of all the group means. This coding system is appropriate when the groups represent natural categories.
</p>
<div class="mw-heading mw-heading3"><h3 id="Two_continuous_independent_variables">Two continuous independent variables</h3></div>
<p>If both of the independent variables are continuous, it is helpful for interpretation to either center or standardize the independent variables, <i>X</i> and <i>Z</i>. (Centering involves subtracting the overall sample mean score from the original score; standardizing does the same followed by dividing by the overall sample standard deviation.) By centering or standardizing the independent variables, the coefficient of <i>X</i> or <i>Z</i> can be interpreted as the effect of that variable on Y at the mean level of the other independent variable.<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup>
</p><p>To probe the interaction effect, it is often helpful to plot the effect of <i>X</i> on <i>Y</i> at low and high values of <i>Z</i> (some people prefer to also plot the effect at moderate values of <i>Z</i>, but this is not necessary). Often values of <i>Z</i> that are one standard deviation above and below the mean are chosen for this, but any sensible values can be used (and in some cases there are more meaningful values to choose). The plot is usually drawn by evaluating the values of <i>Y</i> for high and low values of both <i>X</i> and <i>Z</i>, and creating two lines to represent the effect of <i>X</i> on <i>Y</i> at the two values of <i>Z</i>. Sometimes this is supplemented by simple slope analysis, which determines whether the effect of <i>X</i> on <i>Y</i> is <a href="Statistical_significance" title="Statistical significance">statistically significant</a> at particular values of <i>Z</i>. A common technique for simple slope analysis is the Johnson-Neyman approach.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> Various internet-based tools exist to help researchers plot and interpret such two-way interactions.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup>
</p>
<div class="mw-heading mw-heading3"><h3 id="Higher-level_interactions">Higher-level interactions</h3></div>
<p>The principles for two-way interactions apply when we want to explore three-way or higher-level interactions. For instance, if we have a three-way interaction between <i>A</i>, <i>B</i>, and <i>C</i>, the regression equation will be as follows:
</p>
<dl><dd><span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+b_{7}A\cdot B\cdot C+\varepsilon .}">
<semantics>
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<msub>
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<annotation encoding="application/x-tex">{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+b_{7}A\cdot B\cdot C+\varepsilon .}</annotation>
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</math></span><img src="./28a88dc867bc01db80c5b6e544b385172afaa071.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:75.229ex; height:2.509ex;" alt="{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+b_{7}A\cdot B\cdot C+\varepsilon .}" loading="lazy"></span></dd></dl>
<div class="mw-heading mw-heading3"><h3 id="Spurious_higher-order_effects">Spurious higher-order effects</h3></div>
<p>It is worth noting that the reliability of the higher-order terms depends on the reliability of the lower-order terms. For example, if the reliability for variable <i>A</i> is 0.70, the reliability for variable <i>B</i> is 0.80, and their correlation is <i>r</i> = 0.2, then the reliability for the interaction variable <i>A</i> * <i>B</i> is <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle ((0.7\times 0.8)+0.2^{2})/(1+0.2^{2})=0.577}">
<semantics>
<mrow class="MJX-TeXAtom-ORD">
<mstyle displaystyle="true" scriptlevel="0">
<mo stretchy="false">(</mo>
<mo stretchy="false">(</mo>
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<mo stretchy="false">)</mo>
<mo>+</mo>
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<annotation encoding="application/x-tex">{\displaystyle ((0.7\times 0.8)+0.2^{2})/(1+0.2^{2})=0.577}</annotation>
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</math></span><img src="./3f63de0ec0ced4dbe79bf79ed002071c3ab74633.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.838ex; width:38.665ex; height:3.176ex;" alt="{\displaystyle ((0.7\times 0.8)+0.2^{2})/(1+0.2^{2})=0.577}" loading="lazy"></span>.<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> In this case, low reliability of the interaction term leads to low power; therefore, we may not be able to find the interaction effects between A and B that actually exist. The solution for this problem is to use highly reliable measures for each independent variable.
</p><p>Another caveat for interpreting the interaction effects is that when variable <i>A</i> and variable <i>B</i> are highly correlated, then the <i>A</i> * <i>B</i> term will be highly correlated with the <a href="Omitted-variable_bias" title="Omitted-variable bias">omitted variable</a> <i>A</i><sup>2</sup>; consequently what appears to be a significant moderation effect might actually be a significant nonlinear effect of <i>A</i> alone. If this is the case, it is worth testing a nonlinear regression model by adding nonlinear terms in individual variables into the moderated regression analysis to see if the interactions remain significant. If the interaction effect <i>A</i>*<i>B</i> is still significant, we will be more confident in saying that there is indeed a moderation effect; however, if the interaction effect is no longer significant after adding the nonlinear term, we will be less certain about the existence of a moderation effect and the nonlinear model will be preferred because it is more parsimonious.
</p><p>Moderated regression analyses also tend to include additional variables, which are conceptualized as covariates of no interest. However, the presence of these covariates can induce spurious effects when either (1) the covariate (<i>C</i>) is correlated with one of the primary variables of interest (e.g. variable <i>A</i> or <i>B</i>), or (2) when the covariate itself is a moderator of the correlation between either <i>A</i> or <i>B</i> with <i>Y</i>.<sup id="cite_ref-14" class="reference"><a href="#cite_note-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-15" class="reference"><a href="#cite_note-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-16" class="reference"><a href="#cite_note-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> The solution is to include additional interaction terms in the model, for the interaction between each confounder and the primary variables as follows:
</p>
<dl><dd><span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+\varepsilon }">
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<annotation encoding="application/x-tex">{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+\varepsilon }</annotation>
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</math></span><img src="./a0aae1c874126004a438434b6ca01c78f89e4fac.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.671ex; width:61.058ex; height:2.509ex;" alt="{\displaystyle Y=b_{0}+b_{1}A+b_{2}B+b_{3}C+b_{4}A\cdot B+b_{5}A\cdot C+b_{6}B\cdot C+\varepsilon }" loading="lazy"></span></dd></dl>
<div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2></div>
<ul><li><a href="Omitted-variable_bias" title="Omitted-variable bias">Omitted-variable bias</a></li></ul>
<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>
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</style><div class="reflist">
<div class="mw-references-wrap mw-references-columns"><ol class="references">
<li id="cite_note-cohen-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-cohen_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-cohen_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-cohen_1-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-cohen_1-3"><sup><i><b>d</b></i></sup></a> <a href="#cite_ref-cohen_1-4"><sup><i><b>e</b></i></sup></a></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">
/* start https://en.wikipedia.org/ */
.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("./mw/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("./mw/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("./mw/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("./mw/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}
/* end https://en.wikipedia.org/ */
</style><cite id="CITEREFCohen,_JacobCohen,_PatriciaLeona_S._AikenWest,_Stephen_H.2003" class="citation book cs1">Cohen, Jacob; Cohen, Patricia; <a href="Leona_S._Aiken" title="Leona S. Aiken">Leona S. Aiken</a>; West, Stephen H. (2003). <i>Applied multiple regression/correlation analysis for the behavioral sciences</i>. Hillsdale, N.J: L. Erlbaum Associates. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>0-8058-2223-2</bdi>.</cite></span>
</li>
<li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text"><cite id="CITEREFSchandelmaierBrielVaradhanSchmid2020" class="citation journal cs1">Schandelmaier, Stefan; Briel, Matthias; Varadhan, Ravi; Schmid, Christopher H.; Devasenapathy, Niveditha; Hayward, Rodney A.; Gagnier, Joel; Borenstein, Michael; van der Heijden, Geert J.M.G.; Dahabreh, Issa J.; Sun, Xin; Sauerbrei, Willi; Walsh, Michael; Ioannidis, John P.A.; Thabane, Lehana (2020-08-10). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7829020">"Development of the Instrument to assess the Credibility of Effect Modification Analyses (ICEMAN) in randomized controlled trials and meta-analyses"</a>. <i>Canadian Medical Association Journal</i>. <b>192</b> (32): <span class="nowrap">E901 –</span> <span class="nowrap">E906</span>. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1503%2Fcmaj.200077">10.1503/cmaj.200077</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0820-3946">0820-3946</a>. <a href="PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7829020">7829020</a></span>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/32778601">32778601</a>.</cite></span>
</li>
<li id="cite_note-3"><span class="mw-cite-backlink"><b><a href="#cite_ref-3">^</a></b></span> <span class="reference-text">Baron, R. M., & Kenny, D. A. (1986). "The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations", <i><a href="Journal_of_Personality_and_Social_Psychology" title="Journal of Personality and Social Psychology">Journal of Personality and Social Psychology</a>,</i> 5 (6), 1173–1182 (page 1174)</span>
</li>
<li id="cite_note-4"><span class="mw-cite-backlink"><b><a href="#cite_ref-4">^</a></b></span> <span class="reference-text"><cite id="CITEREFIacobucciSchneiderPopovichBakamitsos2016" class="citation journal cs1">Iacobucci, Dawn; Schneider, Matthew J.; Popovich, Deidre L.; Bakamitsos, Georgios A. (2016). <a rel="nofollow" class="external text" href="https://doi.org/10.3758%2Fs13428-015-0624-x">"Mean centering helps alleviate "micro" but not "macro" multicollinearity"</a>. <i>Behavior Research Methods</i>. <b>48</b> (4): <span class="nowrap">1308–</span>1317. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3758%2Fs13428-015-0624-x">10.3758/s13428-015-0624-x</a></span>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1554-3528">1554-3528</a>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/26148824">26148824</a>.</cite></span>
</li>
<li id="cite_note-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-5">^</a></b></span> <span class="reference-text"><cite id="CITEREFOlvera_AstiviaKroc2019" class="citation journal cs1">Olvera Astivia, Oscar L.; Kroc, Edward (2019). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713984">"Centering in Multiple Regression Does Not Always Reduce Multicollinearity: How to Tell When Your Estimates Will Not Benefit From Centering"</a>. <i>Educational and Psychological Measurement</i>. <b>79</b> (5): <span class="nowrap">813–</span>826. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1177%2F0013164418817801">10.1177/0013164418817801</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0013-1644">0013-1644</a>. <a href="PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713984">6713984</a></span>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/31488914">31488914</a>.</cite></span>
</li>
<li id="cite_note-6"><span class="mw-cite-backlink"><b><a href="#cite_ref-6">^</a></b></span> <span class="reference-text"><cite id="CITEREFTaylor" class="citation web cs1">Taylor, Alan. <a rel="nofollow" class="external text" href="http://www.psy.mq.edu.au/psystat/documents/interaction.pdf">"Testing and Interpreting Interactions in Regression-In a Nutshell"</a> <span class="cs1-format">(PDF)</span>.</cite></span>
</li>
<li id="cite_note-7"><span class="mw-cite-backlink"><b><a href="#cite_ref-7">^</a></b></span> <span class="reference-text"><cite id="CITEREFCohen_JacobCohen_PatriciaWest_Stephen_G.Aiken_Leona_S." class="citation book cs1">Cohen Jacob; Cohen Patricia; West Stephen G.; Aiken Leona S. <i>Applied multiple regression/correlation analysis for the behavioral sciences</i> (3. ed.). Mahwah, NJ [u.a.]: Erlbaum. pp. <span class="nowrap">255–</span>301. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>0-8058-2223-2</bdi>.</cite></span>
</li>
<li id="cite_note-8"><span class="mw-cite-backlink"><b><a href="#cite_ref-8">^</a></b></span> <span class="reference-text"><cite id="CITEREFAiken_L.S.,_West.,_S.G.1996" class="citation book cs1">Aiken L.S., West., S.G. (1996). <i>Multiple regression testing and interpretation</i> (1. paperback print. ed.). Newbury Park, Calif. [u.a.]: Sage Publications, Inc. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>0-7619-0712-2</bdi>.</cite><span class="cs1-maint citation-comment"><code class="cs1-code">{{cite book}}</code>: CS1 maint: multiple names: authors list (link)</span></span>
</li>
<li id="cite_note-9"><span class="mw-cite-backlink"><b><a href="#cite_ref-9">^</a></b></span> <span class="reference-text"><cite id="CITEREFCohen_JacobCohen_PatriciaWest_Stephen_G.Aiken_Leona_S.2003" class="citation book cs1">Cohen Jacob; Cohen Patricia; West Stephen G.; Aiken Leona S. (2003). <i>Applied multiple regression/correlation analysis for the behavioral sciences</i> (3. ed.). Mahwah, NJ [u.a.]: Erlbaum. pp. <span class="nowrap">302–</span>353. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>0-8058-2223-2</bdi>.</cite></span>
</li>
<li id="cite_note-10"><span class="mw-cite-backlink"><b><a href="#cite_ref-10">^</a></b></span> <span class="reference-text">Dawson, J. F. (2013). Moderation in management research: What, why, when and how. Journal of Business and Psychology. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2Fs10869-013-9308-7">10.1007/s10869-013-9308-7</a>.</span>
</li>
<li id="cite_note-11"><span class="mw-cite-backlink"><b><a href="#cite_ref-11">^</a></b></span> <span class="reference-text"><cite id="CITEREFJohnsonFay1950" class="citation journal cs1">Johnson, Palmer O.; Fay, Leo C. (1950-12-01). <span class="id-lock-subscription" title="Paid subscription required"><a rel="nofollow" class="external text" href="https://doi.org/10.1007/BF02288864">"The Johnson-Neyman technique, its theory and application"</a></span>. <i>Psychometrika</i>. <b>15</b> (4): <span class="nowrap">349–</span>367. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2FBF02288864">10.1007/BF02288864</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1860-0980">1860-0980</a>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/14797902">14797902</a>. <a href="S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:43748836">43748836</a>.</cite></span>
</li>
<li id="cite_note-12"><span class="mw-cite-backlink"><b><a href="#cite_ref-12">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.jeremydawson.co.uk/slopes.htm">"Interpreting interaction effects"</a>.</cite></span>
</li>
<li id="cite_note-13"><span class="mw-cite-backlink"><b><a href="#cite_ref-13">^</a></b></span> <span class="reference-text"><cite id="CITEREFBusemeyerJones1983" class="citation journal cs1">Busemeyer, Jerome R.; Jones, Lawrence E. (1983). <span class="id-lock-subscription" title="Paid subscription required"><a rel="nofollow" class="external text" href="http://doi.apa.org/getdoi.cfm?doi=10.1037/0033-2909.93.3.549">"Analysis of multiplicative combination rules when the causal variables are measured with error"</a></span>. <i>Psychological Bulletin</i>. <b>93</b> (3): <span class="nowrap">549–</span>562. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1037%2F0033-2909.93.3.549">10.1037/0033-2909.93.3.549</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1939-1455">1939-1455</a>.</cite></span>
</li>
<li id="cite_note-14"><span class="mw-cite-backlink"><b><a href="#cite_ref-14">^</a></b></span> <span class="reference-text"><cite id="CITEREFKeller2014" class="citation journal cs1">Keller, Matthew C. (2014). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859520">"Gene × Environment Interaction Studies Have Not Properly Controlled for Potential Confounders: The Problem and the (Simple) Solution"</a>. <i>Biological Psychiatry</i>. <b>75</b> (1): <span class="nowrap">18–</span>24. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.biopsych.2013.09.006">10.1016/j.biopsych.2013.09.006</a>. <a href="PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859520">3859520</a></span>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/24135711">24135711</a>.</cite></span>
</li>
<li id="cite_note-15"><span class="mw-cite-backlink"><b><a href="#cite_ref-15">^</a></b></span> <span class="reference-text"><cite id="CITEREFYzerbytMullerJudd2004" class="citation journal cs1">Yzerbyt, Vincent Y.; Muller, Dominique; Judd, Charles M. (2004). <span class="id-lock-subscription" title="Paid subscription required"><a rel="nofollow" class="external text" href="https://linkinghub.elsevier.com/retrieve/pii/S0022103103001598">"Adjusting researchers' approach to adjustment: On the use of covariates when testing interactions"</a></span>. <i>Journal of Experimental Social Psychology</i>. <b>40</b> (3): <span class="nowrap">424–</span>431. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.jesp.2003.10.001">10.1016/j.jesp.2003.10.001</a>.</cite></span>
</li>
<li id="cite_note-16"><span class="mw-cite-backlink"><b><a href="#cite_ref-16">^</a></b></span> <span class="reference-text"><cite id="CITEREFHullTedlieLehn1992" class="citation journal cs1">Hull, Jay G.; Tedlie, Judith C.; Lehn, Daniel A. (1992). <span class="id-lock-subscription" title="Paid subscription required"><a rel="nofollow" class="external text" href="http://journals.sagepub.com/doi/10.1177/0146167292182001">"Moderator Variables in Personality Research: The Problem of Controlling for Plausible Alternatives"</a></span>. <i>Personality and Social Psychology Bulletin</i>. <b>18</b> (2): <span class="nowrap">115–</span>117. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1177%2F0146167292182001">10.1177/0146167292182001</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0146-1672">0146-1672</a>. <a href="S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:145366173">145366173</a>.</cite></span>
</li>
</ol></div></div>
<ul><li>Hayes, A. F., & Matthes, J. (2009). "Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations." Behavior Research Methods, Vol. 41, pp. 924–936.</li></ul>
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</style><div id="Statistics654" style="font-size:114%;margin:0 4em"><a href="Statistics" title="Statistics">Statistics</a></div></th></tr><tr><td class="navbox-abovebelow" colspan="2"><div>
<ul><li><a href="Outline_of_statistics" title="Outline of statistics">Outline</a></li>
<li><a href="List_of_statistics_articles" title="List of statistics articles">Index</a></li></ul>
</div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Descriptive_statistics654" style="font-size:114%;margin:0 4em"><a href="Descriptive_statistics" title="Descriptive statistics">Descriptive statistics</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Continuous_probability_distribution" class="mw-redirect" title="Continuous probability distribution">Continuous data</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Central_tendency" title="Central tendency">Center</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Mean" title="Mean">Mean</a>
<ul><li><a href="Arithmetic_mean" title="Arithmetic mean">Arithmetic</a></li>
<li><a href="Arithmetic%E2%80%93geometric_mean" title="Arithmetic–geometric mean">Arithmetic-Geometric</a></li>
<li><a href="Contraharmonic_mean" title="Contraharmonic mean">Contraharmonic</a></li>
<li><a href="Cubic_mean" title="Cubic mean">Cubic</a></li>
<li><a href="Generalized_mean" title="Generalized mean">Generalized/power</a></li>
<li><a href="Geometric_mean" title="Geometric mean">Geometric</a></li>
<li><a href="Harmonic_mean" title="Harmonic mean">Harmonic</a></li>
<li><a href="Heronian_mean" title="Heronian mean">Heronian</a></li>
<li><a href="Heinz_mean" title="Heinz mean">Heinz</a></li>
<li><a href="Lehmer_mean" title="Lehmer mean">Lehmer</a></li></ul></li>
<li><a href="Median" title="Median">Median</a></li>
<li><a href="Mode_(statistics)" title="Mode (statistics)">Mode</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Statistical_dispersion" title="Statistical dispersion">Dispersion</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Average_absolute_deviation" title="Average absolute deviation">Average absolute deviation</a></li>
<li><a href="Coefficient_of_variation" title="Coefficient of variation">Coefficient of variation</a></li>
<li><a href="Interquartile_range" title="Interquartile range">Interquartile range</a></li>
<li><a href="Percentile" title="Percentile">Percentile</a></li>
<li><a href="Range_(statistics)" title="Range (statistics)">Range</a></li>
<li><a href="Standard_deviation" title="Standard deviation">Standard deviation</a></li>
<li><a href="Variance#Sample_variance" title="Variance">Variance</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Shape_of_the_distribution" class="mw-redirect" title="Shape of the distribution">Shape</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Central_limit_theorem" title="Central limit theorem">Central limit theorem</a></li>
<li><a href="Moment_(mathematics)" title="Moment (mathematics)">Moments</a>
<ul><li><a href="Kurtosis" title="Kurtosis">Kurtosis</a></li>
<li><a href="L-moment" title="L-moment">L-moments</a></li>
<li><a href="Skewness" title="Skewness">Skewness</a></li></ul></li></ul>
</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Count_data" title="Count data">Count data</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Index_of_dispersion" title="Index of dispersion">Index of dispersion</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em">Summary tables</th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Contingency_table" title="Contingency table">Contingency table</a></li>
<li><a href="Frequency_distribution" class="mw-redirect" title="Frequency distribution">Frequency distribution</a></li>
<li><a href="Grouped_data" title="Grouped data">Grouped data</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Correlation_and_dependence" class="mw-redirect" title="Correlation and dependence">Dependence</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Partial_correlation" title="Partial correlation">Partial correlation</a></li>
<li><a href="Pearson_correlation_coefficient" title="Pearson correlation coefficient">Pearson product-moment correlation</a></li>
<li><a href="Rank_correlation" title="Rank correlation">Rank correlation</a>
<ul><li><a href="Kendall_rank_correlation_coefficient" title="Kendall rank correlation coefficient">Kendall's τ</a></li>
<li><a href="Spearman's_rank_correlation_coefficient" title="Spearman's rank correlation coefficient">Spearman's ρ</a></li></ul></li>
<li><a href="Scatter_plot" title="Scatter plot">Scatter plot</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Statistical_graphics" title="Statistical graphics">Graphics</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Bar_chart" title="Bar chart">Bar chart</a></li>
<li><a href="Biplot" title="Biplot">Biplot</a></li>
<li><a href="Box_plot" title="Box plot">Box plot</a></li>
<li><a href="Control_chart" title="Control chart">Control chart</a></li>
<li><a href="Correlogram" title="Correlogram">Correlogram</a></li>
<li><a href="Fan_chart_(statistics)" title="Fan chart (statistics)">Fan chart</a></li>
<li><a href="Forest_plot" title="Forest plot">Forest plot</a></li>
<li><a href="Histogram" title="Histogram">Histogram</a></li>
<li><a href="Pie_chart" title="Pie chart">Pie chart</a></li>
<li><a href="Q%E2%80%93Q_plot" title="Q–Q plot">Q–Q plot</a></li>
<li><a href="Radar_chart" title="Radar chart">Radar chart</a></li>
<li><a href="Run_chart" title="Run chart">Run chart</a></li>
<li><a href="Scatter_plot" title="Scatter plot">Scatter plot</a></li>
<li><a href="Stem-and-leaf_display" title="Stem-and-leaf display">Stem-and-leaf display</a></li>
<li><a href="Violin_plot" title="Violin plot">Violin plot</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Data_collection654" style="font-size:114%;margin:0 4em"><a href="Data_collection" title="Data collection">Data collection</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Design_of_experiments" title="Design of experiments">Study design</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Effect_size" title="Effect size">Effect size</a></li>
<li><a href="Missing_data" title="Missing data">Missing data</a></li>
<li><a href="Optimal_design" class="mw-redirect" title="Optimal design">Optimal design</a></li>
<li><a href="Statistical_population" title="Statistical population">Population</a></li>
<li><a href="Replication_(statistics)" title="Replication (statistics)">Replication</a></li>
<li><a href="Sample_size_determination" title="Sample size determination">Sample size determination</a></li>
<li><a href="Statistic" title="Statistic">Statistic</a></li>
<li><a href="Statistical_power" class="mw-redirect" title="Statistical power">Statistical power</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Survey_methodology" title="Survey methodology">Survey methodology</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Sampling_(statistics)" title="Sampling (statistics)">Sampling</a>
<ul><li><a href="Cluster_sampling" title="Cluster sampling">Cluster</a></li>
<li><a href="Stratified_sampling" title="Stratified sampling">Stratified</a></li></ul></li>
<li><a href="Opinion_poll" title="Opinion poll">Opinion poll</a></li>
<li><a href="Questionnaire" title="Questionnaire">Questionnaire</a></li>
<li><a href="Standard_error" title="Standard error">Standard error</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Experiment" title="Experiment">Controlled experiments</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Blocking_(statistics)" title="Blocking (statistics)">Blocking</a></li>
<li><a href="Factorial_experiment" title="Factorial experiment">Factorial experiment</a></li>
<li><a href="Interaction_(statistics)" title="Interaction (statistics)">Interaction</a></li>
<li><a href="Random_assignment" title="Random assignment">Random assignment</a></li>
<li><a href="Randomized_controlled_trial" title="Randomized controlled trial">Randomized controlled trial</a></li>
<li><a href="Randomized_experiment" title="Randomized experiment">Randomized experiment</a></li>
<li><a href="Scientific_control" title="Scientific control">Scientific control</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em">Adaptive designs</th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Adaptive_clinical_trial" class="mw-redirect" title="Adaptive clinical trial">Adaptive clinical trial</a></li>
<li><a href="Stochastic_approximation" title="Stochastic approximation">Stochastic approximation</a></li>
<li><a href="Up-and-Down_Designs" class="mw-redirect" title="Up-and-Down Designs">Up-and-down designs</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Observational_study" title="Observational study">Observational studies</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Cohort_study" title="Cohort study">Cohort study</a></li>
<li><a href="Cross-sectional_study" title="Cross-sectional study">Cross-sectional study</a></li>
<li><a href="Natural_experiment" title="Natural experiment">Natural experiment</a></li>
<li><a href="Quasi-experiment" title="Quasi-experiment">Quasi-experiment</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Statistical_inference654" style="font-size:114%;margin:0 4em"><a href="Statistical_inference" title="Statistical inference">Statistical inference</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Statistical_theory" title="Statistical theory">Statistical theory</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Population_(statistics)" class="mw-redirect" title="Population (statistics)">Population</a></li>
<li><a href="Statistic" title="Statistic">Statistic</a></li>
<li><a href="Probability_distribution" title="Probability distribution">Probability distribution</a></li>
<li><a href="Sampling_distribution" title="Sampling distribution">Sampling distribution</a>
<ul><li><a href="Order_statistic" title="Order statistic">Order statistic</a></li></ul></li>
<li><a href="Empirical_distribution_function" title="Empirical distribution function">Empirical distribution</a>
<ul><li><a href="Density_estimation" title="Density estimation">Density estimation</a></li></ul></li>
<li><a href="Statistical_model" title="Statistical model">Statistical model</a>
<ul><li><a href="Model_specification" class="mw-redirect" title="Model specification">Model specification</a></li>
<li><a href="Lp_space" title="Lp space">L<sup><i>p</i></sup> space</a></li></ul></li>
<li><a href="Statistical_parameter" title="Statistical parameter">Parameter</a>
<ul><li><a href="Location_parameter" title="Location parameter">location</a></li>
<li><a href="Scale_parameter" title="Scale parameter">scale</a></li>
<li><a href="Shape_parameter" title="Shape parameter">shape</a></li></ul></li>
<li><a href="Parametric_statistics" title="Parametric statistics">Parametric family</a>
<ul><li><a href="Likelihood_function" title="Likelihood function">Likelihood</a> <a href="Monotone_likelihood_ratio" title="Monotone likelihood ratio"><span style="font-size: 85%;">(monotone)</span></a></li>
<li><a href="Location%E2%80%93scale_family" title="Location–scale family">Location–scale family</a></li>
<li><a href="Exponential_family" title="Exponential family">Exponential family</a></li></ul></li>
<li><a href="Completeness_(statistics)" title="Completeness (statistics)">Completeness</a></li>
<li><a href="Sufficient_statistic" title="Sufficient statistic">Sufficiency</a></li>
<li><a href="Plug-in_principle" class="mw-redirect" title="Plug-in principle">Statistical functional</a>
<ul><li><a href="Bootstrapping_(statistics)" title="Bootstrapping (statistics)">Bootstrap</a></li>
<li><a href="U-statistic" title="U-statistic">U</a></li>
<li><a href="V-statistic" title="V-statistic">V</a></li></ul></li>
<li><a href="Optimal_decision" title="Optimal decision">Optimal decision</a>
<ul><li><a href="Loss_function" title="Loss function">loss function</a></li></ul></li>
<li><a href="Efficiency_(statistics)" title="Efficiency (statistics)">Efficiency</a></li>
<li><a href="Statistical_distance" title="Statistical distance">Statistical distance</a>
<ul><li><a href="Divergence_(statistics)" title="Divergence (statistics)">divergence</a></li></ul></li>
<li><a href="Asymptotic_theory_(statistics)" title="Asymptotic theory (statistics)">Asymptotics</a></li>
<li><a href="Robust_statistics" title="Robust statistics">Robustness</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Frequentist_inference" title="Frequentist inference">Frequentist inference</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Point_estimation" title="Point estimation">Point estimation</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Estimating_equations" title="Estimating equations">Estimating equations</a>
<ul><li><a href="Maximum_likelihood" class="mw-redirect" title="Maximum likelihood">Maximum likelihood</a></li>
<li><a href="Method_of_moments_(statistics)" title="Method of moments (statistics)">Method of moments</a></li>
<li><a href="M-estimator" title="M-estimator">M-estimator</a></li>
<li><a href="Minimum_distance_estimation" class="mw-redirect" title="Minimum distance estimation">Minimum distance</a></li></ul></li>
<li><a href="Bias_of_an_estimator" title="Bias of an estimator">Unbiased estimators</a>
<ul><li><a href="Minimum-variance_unbiased_estimator" title="Minimum-variance unbiased estimator">Mean-unbiased minimum-variance</a>
<ul><li><a href="Rao%E2%80%93Blackwell_theorem" title="Rao–Blackwell theorem">Rao–Blackwellization</a></li>
<li><a href="Lehmann%E2%80%93Scheff%C3%A9_theorem" title="Lehmann–Scheffé theorem">Lehmann–Scheffé theorem</a></li></ul></li>
<li><a href="Median-unbiased_estimator" class="mw-redirect" title="Median-unbiased estimator">Median unbiased</a></li></ul></li>
<li><a href="Plug-in_principle" class="mw-redirect" title="Plug-in principle">Plug-in</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Interval_estimation" title="Interval estimation">Interval estimation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Confidence_interval" title="Confidence interval">Confidence interval</a></li>
<li><a href="Pivotal_quantity" title="Pivotal quantity">Pivot</a></li>
<li><a href="Likelihood_interval" class="mw-redirect" title="Likelihood interval">Likelihood interval</a></li>
<li><a href="Prediction_interval" title="Prediction interval">Prediction interval</a></li>
<li><a href="Tolerance_interval" title="Tolerance interval">Tolerance interval</a></li>
<li><a href="Resampling_(statistics)" title="Resampling (statistics)">Resampling</a>
<ul><li><a href="Bootstrapping_(statistics)" title="Bootstrapping (statistics)">Bootstrap</a></li>
<li><a href="Jackknife_resampling" title="Jackknife resampling">Jackknife</a></li></ul></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Statistical_hypothesis_testing" class="mw-redirect" title="Statistical hypothesis testing">Testing hypotheses</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="One-_and_two-tailed_tests" title="One- and two-tailed tests">1- & 2-tails</a></li>
<li><a href="Power_(statistics)" title="Power (statistics)">Power</a>
<ul><li><a href="Uniformly_most_powerful_test" title="Uniformly most powerful test">Uniformly most powerful test</a></li></ul></li>
<li><a href="Permutation_test" title="Permutation test">Permutation test</a>
<ul><li><a href="Randomization_test" class="mw-redirect" title="Randomization test">Randomization test</a></li></ul></li>
<li><a href="Multiple_comparisons" class="mw-redirect" title="Multiple comparisons">Multiple comparisons</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Parametric_statistics" title="Parametric statistics">Parametric tests</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Likelihood-ratio_test" title="Likelihood-ratio test">Likelihood-ratio</a></li>
<li><a href="Score_test" title="Score test">Score/Lagrange multiplier</a></li>
<li><a href="Wald_test" title="Wald test">Wald</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="List_of_statistical_tests" title="List of statistical tests">Specific tests</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><td colspan="2" class="navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Z-test" title="Z-test"><i>Z</i>-test <span style="font-size: 85%;">(normal)</span></a></li>
<li><a href="Student's_t-test" title="Student's t-test">Student's <i>t</i>-test</a></li>
<li><a href="F-test" title="F-test"><i>F</i>-test</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Goodness_of_fit" title="Goodness of fit">Goodness of fit</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Chi-squared_test" title="Chi-squared test">Chi-squared</a></li>
<li><a href="G-test" title="G-test"><i>G</i>-test</a></li>
<li><a href="Kolmogorov%E2%80%93Smirnov_test" title="Kolmogorov–Smirnov test">Kolmogorov–Smirnov</a></li>
<li><a href="Anderson%E2%80%93Darling_test" title="Anderson–Darling test">Anderson–Darling</a></li>
<li><a href="Lilliefors_test" title="Lilliefors test">Lilliefors</a></li>
<li><a href="Jarque%E2%80%93Bera_test" title="Jarque–Bera test">Jarque–Bera</a></li>
<li><a href="Shapiro%E2%80%93Wilk_test" title="Shapiro–Wilk test">Normality <span style="font-size: 85%;">(Shapiro–Wilk)</span></a></li>
<li><a href="Likelihood-ratio_test" title="Likelihood-ratio test">Likelihood-ratio test</a></li>
<li><a href="Model_selection" title="Model selection">Model selection</a>
<ul><li><a href="Cross-validation_(statistics)" title="Cross-validation (statistics)">Cross validation</a></li>
<li><a href="Akaike_information_criterion" title="Akaike information criterion">AIC</a></li>
<li><a href="Bayesian_information_criterion" title="Bayesian information criterion">BIC</a></li></ul></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Rank_statistics" class="mw-redirect" title="Rank statistics">Rank statistics</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Sign_test" title="Sign test">Sign</a>
<ul><li><a href="Sample_median" class="mw-redirect" title="Sample median">Sample median</a></li></ul></li>
<li><a href="Wilcoxon_signed-rank_test" title="Wilcoxon signed-rank test">Signed rank <span style="font-size: 85%;">(Wilcoxon)</span></a>
<ul><li><a href="Hodges%E2%80%93Lehmann_estimator" title="Hodges–Lehmann estimator">Hodges–Lehmann estimator</a></li></ul></li>
<li><a href="Mann%E2%80%93Whitney_U_test" title="Mann–Whitney U test">Rank sum <span style="font-size: 85%;">(Mann–Whitney)</span></a></li>
<li><a href="Nonparametric_statistics" title="Nonparametric statistics">Nonparametric</a> <a href="Analysis_of_variance" title="Analysis of variance">anova</a>
<ul><li><a href="Kruskal%E2%80%93Wallis_test" title="Kruskal–Wallis test">1-way <span style="font-size: 85%;">(Kruskal–Wallis)</span></a></li>
<li><a href="Friedman_test" title="Friedman test">2-way <span style="font-size: 85%;">(Friedman)</span></a></li>
<li><a href="Jonckheere's_trend_test" title="Jonckheere's trend test">Ordered alternative <span style="font-size: 85%;">(Jonckheere–Terpstra)</span></a></li></ul></li>
<li><a href="Van_der_Waerden_test" title="Van der Waerden test">Van der Waerden test</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Bayesian_inference" title="Bayesian inference">Bayesian inference</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Bayesian_probability" title="Bayesian probability">Bayesian probability</a>
<ul><li><a href="Prior_probability" title="Prior probability">prior</a></li>
<li><a href="Posterior_probability" title="Posterior probability">posterior</a></li></ul></li>
<li><a href="Credible_interval" title="Credible interval">Credible interval</a></li>
<li><a href="Bayes_factor" title="Bayes factor">Bayes factor</a></li>
<li><a href="Bayes_estimator" title="Bayes estimator">Bayesian estimator</a>
<ul><li><a href="Maximum_a_posteriori_estimation" title="Maximum a posteriori estimation">Maximum posterior estimator</a></li></ul></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="CorrelationRegression_analysis654" style="font-size:114%;margin:0 4em"><div class="hlist"><ul><li><a href="Correlation_and_dependence" class="mw-redirect" title="Correlation and dependence">Correlation</a></li><li><a href="Regression_analysis" title="Regression analysis">Regression analysis</a></li></ul></div></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Correlation_and_dependence" class="mw-redirect" title="Correlation and dependence">Correlation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Pearson_product-moment_correlation_coefficient" class="mw-redirect" title="Pearson product-moment correlation coefficient">Pearson product-moment</a></li>
<li><a href="Partial_correlation" title="Partial correlation">Partial correlation</a></li>
<li><a href="Confounding" title="Confounding">Confounding variable</a></li>
<li><a href="Coefficient_of_determination" title="Coefficient of determination">Coefficient of determination</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Regression_analysis" title="Regression analysis">Regression analysis</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Errors_and_residuals" title="Errors and residuals">Errors and residuals</a></li>
<li><a href="Regression_validation" title="Regression validation">Regression validation</a></li>
<li><a href="Mixed_model" title="Mixed model">Mixed effects models</a></li>
<li><a href="Simultaneous_equations_model" title="Simultaneous equations model">Simultaneous equations models</a></li>
<li><a href="Multivariate_adaptive_regression_splines" class="mw-redirect" title="Multivariate adaptive regression splines">Multivariate adaptive regression splines (MARS)</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Linear_regression" title="Linear regression">Linear regression</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Simple_linear_regression" title="Simple linear regression">Simple linear regression</a></li>
<li><a href="Ordinary_least_squares" title="Ordinary least squares">Ordinary least squares</a></li>
<li><a href="General_linear_model" title="General linear model">General linear model</a></li>
<li><a href="Bayesian_linear_regression" title="Bayesian linear regression">Bayesian regression</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em">Non-standard predictors</th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Nonlinear_regression" title="Nonlinear regression">Nonlinear regression</a></li>
<li><a href="Nonparametric_regression" title="Nonparametric regression">Nonparametric</a></li>
<li><a href="Semiparametric_regression" title="Semiparametric regression">Semiparametric</a></li>
<li><a href="Isotonic_regression" title="Isotonic regression">Isotonic</a></li>
<li><a href="Robust_regression" title="Robust regression">Robust</a></li>
<li><a href="Homoscedasticity_and_heteroscedasticity" title="Homoscedasticity and heteroscedasticity">Homoscedasticity and Heteroscedasticity</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Generalized_linear_model" title="Generalized linear model">Generalized linear model</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Exponential_family" title="Exponential family">Exponential families</a></li>
<li><a href="Logistic_regression" title="Logistic regression">Logistic <span style="font-size: 85%;">(Bernoulli)</span></a> / <a href="Binomial_regression" title="Binomial regression">Binomial</a> / <a href="Poisson_regression" title="Poisson regression">Poisson regressions</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Partition_of_sums_of_squares" title="Partition of sums of squares">Partition of variance</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Analysis_of_variance" title="Analysis of variance">Analysis of variance (ANOVA, anova)</a></li>
<li><a href="Analysis_of_covariance" title="Analysis of covariance">Analysis of covariance</a></li>
<li><a href="Multivariate_analysis_of_variance" title="Multivariate analysis of variance">Multivariate ANOVA</a></li>
<li><a href="Degrees_of_freedom_(statistics)" title="Degrees of freedom (statistics)">Degrees of freedom</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Categorical_/_multivariate_/_time-series_/_survival_analysis654" style="font-size:114%;margin:0 4em"><a href="Categorical_variable" title="Categorical variable">Categorical</a> / <a href="Multivariate_statistics" title="Multivariate statistics">multivariate</a> / <a href="Time_series" title="Time series">time-series</a> / <a href="Survival_analysis" title="Survival analysis">survival analysis</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Categorical_variable" title="Categorical variable">Categorical</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Cohen's_kappa" title="Cohen's kappa">Cohen's kappa</a></li>
<li><a href="Contingency_table" title="Contingency table">Contingency table</a></li>
<li><a href="Graphical_model" title="Graphical model">Graphical model</a></li>
<li><a href="Poisson_regression" title="Poisson regression">Log-linear model</a></li>
<li><a href="McNemar's_test" title="McNemar's test">McNemar's test</a></li>
<li><a href="Cochran%E2%80%93Mantel%E2%80%93Haenszel_statistics" title="Cochran–Mantel–Haenszel statistics">Cochran–Mantel–Haenszel statistics</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Multivariate_statistics" title="Multivariate statistics">Multivariate</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="General_linear_model" title="General linear model">Regression</a></li>
<li><a href="Multivariate_analysis_of_variance" title="Multivariate analysis of variance">Manova</a></li>
<li><a href="Principal_component_analysis" title="Principal component analysis">Principal components</a></li>
<li><a href="Canonical_correlation" title="Canonical correlation">Canonical correlation</a></li>
<li><a href="Linear_discriminant_analysis" title="Linear discriminant analysis">Discriminant analysis</a></li>
<li><a href="Cluster_analysis" title="Cluster analysis">Cluster analysis</a></li>
<li><a href="Statistical_classification" title="Statistical classification">Classification</a></li>
<li><a href="Structural_equation_modeling" title="Structural equation modeling">Structural equation model</a>
<ul><li><a href="Factor_analysis" title="Factor analysis">Factor analysis</a></li></ul></li>
<li><a href="Multivariate_distribution" class="mw-redirect" title="Multivariate distribution">Multivariate distributions</a>
<ul><li><a href="Elliptical_distribution" title="Elliptical distribution">Elliptical distributions</a>
<ul><li><a href="Multivariate_normal_distribution" title="Multivariate normal distribution">Normal</a></li></ul></li></ul></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Time_series" title="Time series">Time-series</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;">General</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Decomposition_of_time_series" title="Decomposition of time series">Decomposition</a></li>
<li><a href="Trend_estimation" class="mw-redirect" title="Trend estimation">Trend</a></li>
<li><a href="Stationary_process" title="Stationary process">Stationarity</a></li>
<li><a href="Seasonal_adjustment" title="Seasonal adjustment">Seasonal adjustment</a></li>
<li><a href="Exponential_smoothing" title="Exponential smoothing">Exponential smoothing</a></li>
<li><a href="Cointegration" title="Cointegration">Cointegration</a></li>
<li><a href="Structural_break" title="Structural break">Structural break</a></li>
<li><a href="Granger_causality" title="Granger causality">Granger causality</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;">Specific tests</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Dickey%E2%80%93Fuller_test" title="Dickey–Fuller test">Dickey–Fuller</a></li>
<li><a href="Johansen_test" title="Johansen test">Johansen</a></li>
<li><a href="Ljung%E2%80%93Box_test" title="Ljung–Box test">Q-statistic <span style="font-size: 85%;">(Ljung–Box)</span></a></li>
<li><a href="Durbin%E2%80%93Watson_statistic" title="Durbin–Watson statistic">Durbin–Watson</a></li>
<li><a href="Breusch%E2%80%93Godfrey_test" title="Breusch–Godfrey test">Breusch–Godfrey</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Time_domain" title="Time domain">Time domain</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Autocorrelation" title="Autocorrelation">Autocorrelation (ACF)</a>
<ul><li><a href="Partial_autocorrelation_function" title="Partial autocorrelation function">partial (PACF)</a></li></ul></li>
<li><a href="Cross-correlation" title="Cross-correlation">Cross-correlation (XCF)</a></li>
<li><a href="Autoregressive%E2%80%93moving-average_model" class="mw-redirect" title="Autoregressive–moving-average model">ARMA model</a></li>
<li><a href="Box%E2%80%93Jenkins_method" title="Box–Jenkins method">ARIMA model <span style="font-size: 85%;">(Box–Jenkins)</span></a></li>
<li><a href="Autoregressive_conditional_heteroskedasticity" title="Autoregressive conditional heteroskedasticity">Autoregressive conditional heteroskedasticity (ARCH)</a></li>
<li><a href="Vector_autoregression" title="Vector autoregression">Vector autoregression (VAR)</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Frequency_domain" title="Frequency domain">Frequency domain</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Spectral_density_estimation" title="Spectral density estimation">Spectral density estimation</a></li>
<li><a href="Fourier_analysis" title="Fourier analysis">Fourier analysis</a></li>
<li><a href="Least-squares_spectral_analysis" title="Least-squares spectral analysis">Least-squares spectral analysis</a></li>
<li><a href="Wavelet" title="Wavelet">Wavelet</a></li>
<li><a href="Whittle_likelihood" title="Whittle likelihood">Whittle likelihood</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Survival_analysis" title="Survival analysis">Survival</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Survival_function" title="Survival function">Survival function</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Kaplan%E2%80%93Meier_estimator" title="Kaplan–Meier estimator">Kaplan–Meier estimator (product limit)</a></li>
<li><a href="Proportional_hazards_model" title="Proportional hazards model">Proportional hazards models</a></li>
<li><a href="Accelerated_failure_time_model" title="Accelerated failure time model">Accelerated failure time (AFT) model</a></li>
<li><a href="First-hitting-time_model" title="First-hitting-time model">First hitting time</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;"><a href="Failure_rate" title="Failure rate">Hazard function</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Nelson%E2%80%93Aalen_estimator" title="Nelson–Aalen estimator">Nelson–Aalen estimator</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%;font-weight:normal;">Test</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Log-rank_test" class="mw-redirect" title="Log-rank test">Log-rank test</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks mw-collapsible mw-collapsed navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Applications654" style="font-size:114%;margin:0 4em"><a href="List_of_fields_of_application_of_statistics" title="List of fields of application of statistics">Applications</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Biostatistics" title="Biostatistics">Biostatistics</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Bioinformatics" title="Bioinformatics">Bioinformatics</a></li>
<li><a href="Clinical_trial" title="Clinical trial">Clinical trials</a> / <a href="Clinical_study_design" title="Clinical study design">studies</a></li>
<li><a href="Epidemiology" title="Epidemiology">Epidemiology</a></li>
<li><a href="Medical_statistics" title="Medical statistics">Medical statistics</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Engineering_statistics" title="Engineering statistics">Engineering statistics</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Chemometrics" title="Chemometrics">Chemometrics</a></li>
<li><a href="Methods_engineering" title="Methods engineering">Methods engineering</a></li>
<li><a href="Probabilistic_design" title="Probabilistic design">Probabilistic design</a></li>
<li><a href="Statistical_process_control" title="Statistical process control">Process</a> / <a href="Quality_control" title="Quality control">quality control</a></li>
<li><a href="Reliability_engineering" title="Reliability engineering">Reliability</a></li>
<li><a href="System_identification" title="System identification">System identification</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Social_statistics" title="Social statistics">Social statistics</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Actuarial_science" title="Actuarial science">Actuarial science</a></li>
<li><a href="Census" title="Census">Census</a></li>
<li><a href="Crime_statistics" title="Crime statistics">Crime statistics</a></li>
<li><a href="Demographic_statistics" title="Demographic statistics">Demography</a></li>
<li><a href="Econometrics" title="Econometrics">Econometrics</a></li>
<li><a href="Jurimetrics" title="Jurimetrics">Jurimetrics</a></li>
<li><a href="National_accounts" title="National accounts">National accounts</a></li>
<li><a href="Official_statistics" title="Official statistics">Official statistics</a></li>
<li><a href="Population_statistics" class="mw-redirect" title="Population statistics">Population statistics</a></li>
<li><a href="Psychometrics" title="Psychometrics">Psychometrics</a></li></ul>
</div></td></tr><tr><th scope="row" class="navbox-group" style="width:12.5em"><a href="Spatial_analysis" title="Spatial analysis">Spatial statistics</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="padding:0"><div style="padding:0 0.25em">
<ul><li><a href="Cartography" title="Cartography">Cartography</a></li>
<li><a href="Environmental_statistics" title="Environmental statistics">Environmental statistics</a></li>
<li><a href="Geographic_information_system" title="Geographic information system">Geographic information system</a></li>
<li><a href="Geostatistics" title="Geostatistics">Geostatistics</a></li>
<li><a href="Kriging" title="Kriging">Kriging</a></li></ul>
</div></td></tr></tbody></table><div></div></td></tr></tbody></table><div></div></td></tr><tr><td class="navbox-abovebelow" colspan="2"><div>
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<li><span class="noviewer" typeof="mw:File"><span title="Commons page"></span></span><b><a href="https://commons.wikimedia.org/wiki/Category:Statistics" class="extiw external" title="commons:Category:Statistics">Commons</a></b></li>
<li><span class="noviewer" typeof="mw:File"><span title="WikiProject"></span></span> <b>WikiProject</b></li></ul>
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