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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
\usepackage{amsmath}            % Symbols
\usepackage{MnSymbol}           % Symbols
\usepackage{wasysym}            % Symbols
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% Document Info
\author{Robyn.jll}
\pdfinfo{
  /Title (step-5.pdf)
  /Creator (Cheatography)
  /Author (Robyn.jll)
  /Subject (Step 5 Cheat Sheet)
}

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% Commands
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% Header and Footer
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\fancyhead[L]{
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
    \SetRowColor{DarkBackground}
    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\end{tabulary}
\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Step 5 Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Robyn.jll} via \textcolor{DarkBackground}{\uline{cheatography.com/146401/cs/31684/}}}
\end{tabulary}
\end{multicols}}

\fancyfoot[L]{ \footnotesize
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}Robyn.jll \\
  \uline{cheatography.com/robyn-jll} \\
  \end{tabulary}
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\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 14th April, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
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  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
\end{tabulary}
\end{multicols}}




\begin{document}
\raggedright
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% Set font size to small. Switch to any value
% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.

\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{p{0.4977 cm} x{4.4793 cm} }
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\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{Statistical significance}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{In hypothesis testing, statistical significance is the main criterion for forming conclusions. You compare your p value to a set significance level (usually 0.05) to decide whether your results are statistically significant or non-significant.} \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
\mymulticolumn{2}{x{5.377cm}}{If a result is statistically significant, that means it's unlikely to be explained solely by chance or random factors. In other words, a statistically significant result has a very low chance of occurring if there were no true effect in a research study.} \tn 
% Row Count 11 (+ 6)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{The p value, or probability value, tells you the statistical significance of a finding. In most studies, a p value of 0.05 or less is considered statistically significant, but this threshold can also be set higher or lower.} \tn 
% Row Count 16 (+ 5)
% Row 3
\SetRowColor{white}
\mymulticolumn{2}{x{5.377cm}}{The significance level, or alpha (α), is a value that the researcher sets in advance as the threshold for statistical significance. It is the maximum risk of making a false positive conclusion (Type I error) that you are willing to accept.} \tn 
% Row Count 21 (+ 5)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{In a hypothesis test, the p value is compared to the significance level to decide whether to reject the null hypothesis.} \tn 
% Row Count 24 (+ 3)
% Row 5
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 & •	If the p value is higher than the significance level, the null hypothesis is not refuted, and the results are not statistically significant. \tn 
% Row Count 28 (+ 4)
% Row 6
\SetRowColor{LightBackground}
 & •	If the p value is lower than the significance level, the results are interpreted as refuting the null hypothesis and reported as statistically significant. \tn 
% Row Count 33 (+ 5)
\end{tabularx}
\par\addvspace{1.3em}

\vfill
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\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{Statistical significance (cont)}}  \tn
% Row 7
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{Usually, the significance level is set to 0.05 or 5\%. That means your results must have a 5\% or lower chance of occurring under the null hypothesis to be considered statistically significant.} \tn 
% Row Count 4 (+ 4)
% Row 8
\SetRowColor{white}
\mymulticolumn{2}{x{5.377cm}}{The significance level can be lowered for a more conservative test. That means an effect has to be larger to be considered statistically significant.} \tn 
% Row Count 7 (+ 3)
% Row 9
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{5.377cm}}{The significance level may also be set higher for significance testing in non-academic marketing or business contexts. This makes the study less rigorous and increases the probability of finding a statistically significant result.} \tn 
% Row Count 12 (+ 5)
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Effect Size}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{indicates the practical significance of your results. It's important to report effect sizes along with your inferential statistics for a complete picture of your results. You should also report interval estimates of effect sizes if you're writing an APA style paper. \newline % Row Count 6 (+ 6)
Effect size tells you how meaningful the relationship between variables or the difference between groups is. It indicates the practical significance of a research outcome. \newline % Row Count 10 (+ 4)
A large effect size means that a research finding has practical significance, while a small effect size indicates limited practical applications.% Row Count 13 (+ 3)
} \tn 
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\begin{tabularx}{5.377cm}{x{1.74195 cm} x{3.23505 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{5.377cm}}{\bf\textcolor{white}{Frequentist vs. Bayesian statistics}}  \tn
% Row 0
\SetRowColor{LightBackground}
Frequentist statistics & emphasizes null hypothesis significance testing and always starts with the assumption of a true null hypothesis. \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
Bayesian statistics & In this approach, you use previous research to continually update your hypotheses based on your expectations and observations. \tn 
% Row Count 10 (+ 5)
% Row 2
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 & Bayes factor compares the relative strength of evidence for the null versus the alternative hypothesis rather than making a conclusion about rejecting the null hypothesis or not. \tn 
% Row Count 17 (+ 7)
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\begin{tabularx}{5.377cm}{X}
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Decision error}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Type I and Type II errors are mistakes made in research conclusions.  \newline % Row Count 2 (+ 2)
A {\bf{Type I error}} means rejecting the null hypothesis when it's actually true, while a {\bf{Type II error}} means failing to reject the null hypothesis when it's false. \newline % Row Count 6 (+ 4)
The probability of making a {\bf{Type I error}} is the significance level, or {\bf{alpha (α)}}, while the probability of making a {\bf{Type II error}} is {\bf{beta (β)}}.  \newline % Row Count 10 (+ 4)
These risks can be minimized through careful planning in your study design.% Row Count 12 (+ 2)
} \tn 
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
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\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Type I \& Type II Error}}  \tn
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\par\addvspace{1.3em}


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

\end{document}