This flowchart helps you determine which of the most common statistics tests you need to use for your analysis. It covers 11 of the most common statistics tests.
This guide helps describe the relative strengths of correlations in terms of their direction and magnitude. It is suitable for Pearson's r and Spearmean's ρ (rho) correlations and uses definitions from the British Medical Journal for guidance.
This guide contains an example of having the same data in long format and wide format. It also explains some differences between the two types of structures.
This guide contains an example of having the same data in long format and wide format. It also explains some differences between the two types of structures.
This guide provides definitions and examples of the six most common Descriptive
Statistics (Mean, Median, Mode, Standard Deviation, Interquartile Range, Range) and explains which statistic you should use for different types of data.
This guide provides definitions of the four parametric assumptions (Normality, Homogenous Variance, Interval, and Independence). It also explains how to test if your data passes each parametric assumption check.
This guide demonstrates an example of a linear regression and shows how you can calculate and determine the extent to which one independent (input/regressor) variable affects a dependent (output/response) variable.
This guide expands on the Correlation Coefficients guide (see above) and helps you visualise nine correlations with different correlation coefficients and significance values.
