The Chi-Square Test shows whether two categorical variables are independent of each other.Read more
The One-Sample T-Test shows whether the mean of a sample is different from a chosen value.Read more
The Independent-Samples T-Test shows whether two independent samples have different means.Read more
The Paired-Samples T-Test shows whether the means of two variables of the same sample are different.Read more
The One-Way ANOVA shows whether three or more independent samples differ in means on a continuous variable.Read more
The Correlation Analysis shows whether two continuous variables have a linear relationship with each other.Read more
The Linear Regression Analysis models the relationship between a continuous dependent and one or more independent variables.Read more
The Logistic Regression Analysis models the relationship between a categorical dependent and one or more independent variables.Read more
The Two-Way ANOVA shows the effects of two categorical independent variables and their interaction on a dependent variable.Read more
The Repeated Measures ANOVA shows whether the means of three or more variables of the same sample are different.Read more
The Reliability Analysis shows whether several questions that belong to the same construct can be taken together to form one reliable scale.Read more
The non-parametric Wilcoxon Signed-Rank Test shows whether the mean ranks of two variables of the same sample are different.Read more
The non-parametric Mann-Whitney U Test shows whether two independent samples differ in mean ranks.Read more
The non-parametric Kruskal-Wallis H Test shows whether three or more independent samples differ in mean ranks.Read more
The non-parametric McNemar Test shows whether two repeated binary variables differ in proportions.Read more
The non-parametric Cochran's Q Test shows whether three or more repeated binary variables differ in proportions.Read more
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