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\author{Robyn.jll}
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  /Title (statistical-tests.pdf)
  /Creator (Cheatography)
  /Author (Robyn.jll)
  /Subject (Statistical Tests Cheat Sheet)
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    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Statistical Tests Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Robyn.jll} via \textcolor{DarkBackground}{\uline{cheatography.com/146401/cs/31818/}}}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}Robyn.jll \\
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 23rd April, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
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\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{x{1.89126 cm} x{3.08574 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 Dependent Variable \& 0 IVs (1 Population)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & One-sample t-test \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & tests if a sample mean differs sig. from a hypothesized value \tn 
% Row Count 6 (+ 3)
% Row 3
\SetRowColor{white}
ordinal or interval & One-sample median test \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & tests if a sample median differs sig. from a hypothesized value \tn 
% Row Count 11 (+ 3)
% Row 5
\SetRowColor{white}
categorial (2 categories) & Binominal Test \tn 
% Row Count 13 (+ 2)
% Row 6
\SetRowColor{LightBackground}
 & tests if the proportion of successes on a two-level categorial dependent variable differs sig. from a hypothesized value \tn 
% Row Count 18 (+ 5)
% Row 7
\SetRowColor{white}
categorial & Chi-square goodness-of-fit \tn 
% Row Count 20 (+ 2)
% Row 8
\SetRowColor{LightBackground}
 & tests if the observed proportions for a categorial variable differ from hypothesized proportions \tn 
% Row Count 24 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.59264 cm} x{3.38436 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1IV with 2 levels (independent groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & 2 independent sample t-test \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & compares the means of a normally distributed interval DV for two independent groups \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
ordinal or interval & Wilcoxon-Mann Whitney test \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & is a non-parametric analog to the independent samples t-test \tn 
% Row Count 12 (+ 3)
% Row 5
\SetRowColor{white}
 & used, when you do not assume that the DV is a normally distributed interval variable \tn 
% Row Count 16 (+ 4)
% Row 6
\SetRowColor{LightBackground}
categorial & Chi-square test \tn 
% Row Count 17 (+ 1)
% Row 7
\SetRowColor{white}
 & to see if there is a relationship between 2 categorial varibales \tn 
% Row Count 20 (+ 3)
% Row 8
\SetRowColor{LightBackground}
 & assumes that each cell has an expected frequency of 5 or more \tn 
% Row Count 23 (+ 3)
% Row 9
\SetRowColor{white}
categorial & Fischer\textbackslash{}`s exact test \tn 
% Row Count 24 (+ 1)
% Row 10
\SetRowColor{LightBackground}
 & same as Chi-square test, but can be used regardless of the expected frequency (expected frequency of 5 or less) \tn 
% Row Count 29 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.59264 cm} x{3.38436 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1IV with 2 or more levels (indep. groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & One-Way ANOVA \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & test for differences in the means of the DV broken down by the levels of the IV \tn 
% Row Count 6 (+ 3)
% Row 3
\SetRowColor{white}
 & used when categorial IV (with one or more categories) an normally distributed interval DV \tn 
% Row Count 10 (+ 4)
% Row 4
\SetRowColor{LightBackground}
ordinal or interval & Kruskal Wallis test \tn 
% Row Count 12 (+ 2)
% Row 5
\SetRowColor{white}
 & is non-parametric version of ANOVA and a generalized form of the Mann-Whitney test since it permits two or more groups \tn 
% Row Count 17 (+ 5)
% Row 6
\SetRowColor{LightBackground}
categorial & Chi-square test \tn 
% Row Count 18 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.59264 cm} x{3.38436 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1IV with 2 or more levels (indep. groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & One-Way ANOVA \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & test for differences in the means of the DV broken down by the levels of the IV \tn 
% Row Count 6 (+ 3)
% Row 3
\SetRowColor{white}
 & used when categorial IV (with one or more categories) an normally distributed interval DV \tn 
% Row Count 10 (+ 4)
% Row 4
\SetRowColor{LightBackground}
ordinal or interval & Kruskal Wallis test \tn 
% Row Count 12 (+ 2)
% Row 5
\SetRowColor{white}
 & is non-parametric version of ANOVA and a generalized form of the Mann-Whitney test since it permits two or more groups \tn 
% Row Count 17 (+ 5)
% Row 6
\SetRowColor{LightBackground}
categorial & Chi-square test \tn 
% Row Count 18 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.59264 cm} x{3.38436 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1IV with 2 (dependent/matched groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & Paired t-test \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & used when you have two related observations and want to see if the means on these two normally distributed interval variables differ from one another \tn 
% Row Count 9 (+ 6)
% Row 3
\SetRowColor{white}
ordinal or interval & Wilcoxon signed rank sum test \tn 
% Row Count 11 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & is non-parametric version of a paired sample t-test \tn 
% Row Count 13 (+ 2)
% Row 5
\SetRowColor{white}
 & used, when you do not wish to assume that the difference between the two variables is the interval and normally distributed \tn 
% Row Count 18 (+ 5)
% Row 6
\SetRowColor{LightBackground}
categorial & McNemar test \tn 
% Row Count 19 (+ 1)
% Row 7
\SetRowColor{white}
 & use if interested in the marginal frequencies of two binary outcomes \tn 
% Row Count 22 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.89126 cm} x{3.08574 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1 IV with 2 or m. lev. (dep./matched g.)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & One-Way repeated measures ANOVA \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & is the equivalent of paired t-test, but allows for 2 or more levels of the categorial variable \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
ordinal or interval & Friedman test \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & use when you have one within-subjects IV with 2 or more levels and a DV that is not interval or normally distributed \tn 
% Row Count 14 (+ 5)
% Row 5
\SetRowColor{white}
categorial (2 categories) & Repeated measures logistic regression \tn 
% Row Count 16 (+ 2)
% Row 6
\SetRowColor{LightBackground}
 & use if you have a binary outcome measured repeatedly for each subject and wish to run a logistic regression that accounts for the effects of multiple measures from a single subject \tn 
% Row Count 24 (+ 8)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.89126 cm} x{3.08574 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 2 or more IVs (indepen. groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & factorial ANOVA \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & use if you have 2 or more categorial IV and a single normally distributed interval DV \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
ordinal or interval & Ordered logistic regression \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & used, when the DV is ordered, but not continuous \tn 
% Row Count 11 (+ 2)
% Row 5
\SetRowColor{white}
categorial (2 categories & Factorial logistic regression \tn 
% Row Count 13 (+ 2)
% Row 6
\SetRowColor{LightBackground}
 & used, when you have 2 or more categorial IV but a dichotomous DV \tn 
% Row Count 16 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.59264 cm} x{3.38436 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1 interval IV}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & Correlation \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & used, when you want to see the relationship between two (or more) normally distributed interval variables \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
interval \& normal & Simple linear regression \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & allows us to look at the linear relationship between one normally distributed interval IV and one normally distributed interval DV \tn 
% Row Count 14 (+ 5)
% Row 5
\SetRowColor{white}
ordinal or interval & Non-parametric correlation (Spearman) \tn 
% Row Count 16 (+ 2)
% Row 6
\SetRowColor{LightBackground}
 & used, when one or both of the variables are not assumed to be normally distributed and interval \tn 
% Row Count 20 (+ 4)
% Row 7
\SetRowColor{white}
 & the values of the variables are converted in ranks and then correlated \tn 
% Row Count 23 (+ 3)
% Row 8
\SetRowColor{LightBackground}
categorial & Simple logistic regression \tn 
% Row Count 24 (+ 1)
% Row 9
\SetRowColor{white}
 & assumes that the outcome variable is binary \tn 
% Row Count 26 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.4931 cm} x{3.4839 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{1 DV \& 1 or m. interval IV/ 1 or m. categ. IVs}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & Multiple Regression \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & similar to simple regression, except that in multiple regression you have more that one IV in the equation \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
interval \& normal & Analysis of Covariance \tn 
% Row Count 9 (+ 2)
% Row 4
\SetRowColor{LightBackground}
 & like ANOVA, except in addition to the categorial IV you also have continuous IV \tn 
% Row Count 12 (+ 3)
% Row 5
\SetRowColor{white}
categorial & Multiple logistic regression \tn 
% Row Count 13 (+ 1)
% Row 6
\SetRowColor{LightBackground}
 & like simple regression, except that there are 2 or more IV \tn 
% Row Count 16 (+ 3)
% Row 7
\SetRowColor{white}
 & IV can be dummy or interval variables, but cannot be categorial variables (if, should be coded into 1 or more dummy variables) \tn 
% Row Count 21 (+ 5)
% Row 8
\SetRowColor{LightBackground}
categorial & Discriminant analysis \tn 
% Row Count 22 (+ 1)
% Row 9
\SetRowColor{white}
 & used, when you have one or more normally distributed interval IV and a categorial DV \tn 
% Row Count 25 (+ 3)
% Row 10
\SetRowColor{LightBackground}
 & is a multivariate technique that considers the latent dimensions in the IV for predicting group membership in the categorial DV \tn 
% Row Count 30 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.4931 cm} x{3.4839 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{2+ DV \& 1 IV with 2 or more levels (indep. groups)}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & One-way MANOVA \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & like ANOVA, except that there are 2 or more DV. \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
 & there is one categorial IV and two or more DV \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
interval \& normal & Multivariate multiple linear regression \tn 
% Row Count 9 (+ 2)
% Row 5
\SetRowColor{white}
 & used, when you have two or more DV that are to be predicted from two or more IV \tn 
% Row Count 12 (+ 3)
% Row 6
\SetRowColor{LightBackground}
interval \& normal & Factor analysis \tn 
% Row Count 14 (+ 2)
% Row 7
\SetRowColor{white}
 & is a form of exploratory multivariate analysis that is used to either reduce the number of variables in a model or to detect relationships amongst variables \tn 
% Row Count 20 (+ 6)
% Row 8
\SetRowColor{LightBackground}
 & all variabales need to be interval and assumed to be normally distributed \tn 
% Row Count 23 (+ 3)
% Row 9
\SetRowColor{white}
 & goal is to try to identify factors which underlie the variables \tn 
% Row Count 26 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{x{1.4931 cm} x{3.4839 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{2 sets of 2+ DV \& 0 IV}}  \tn
% Row 0
\SetRowColor{LightBackground}
{\bf{DV}} & {\bf{Test}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
interval \& normal & Canonical correlation \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
 & is a multivariate technique used to examine the relationship between two groups of variables \tn 
% Row Count 7 (+ 4)
% Row 3
\SetRowColor{white}
 & for each set of variables, it creates latent variables and looks at the relationship among the latent variables \tn 
% Row Count 11 (+ 4)
% Row 4
\SetRowColor{LightBackground}
 & assumes that all variables in the model are interval and normally distributed \tn 
% Row Count 14 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}