By Kanza Khan
A Statistical F Test uses an F Statistic to compare two variances, s1 and s2, by dividing them. The result is always a positive number (because variances are always positive). Variance measures variability from the average or mean. Measures how far data is spread out from the mean.
F statistic is a value you get when you run an ANOVA test or a regression analysis to find out if the means between two populations are significantly different. It’s similar to a T statistic from a T-Test; A T-test will tell you if a single variable is statistically significant and an F test will tell you if a group of variables are jointly significant.
The value you calculate from your data is called the F Statistic or F value (without the “critical” part).. The F critical value is a specific value you compare your f-value to.
In general, if your calculated F value in a test is larger than your F critical value, you can reject the null hypothesis.
A Bland Altman plot is also known as the TURKEY-MEAN DIFFERENCE plot. It determines difference between two quantitative measurements . It also measures mean difference along the limits of agreement.
In this analysis, a pair of observations is made from the same subject, with two different methods. Subsequently, the means and differences of these pairs of values for each subject are displayed in a scatter plot. The plot usually also shows a line for the estimated mean difference between the two methods (a measure of the bias between the two methods), and lines indicating the BA LoA (within which approximately 95% of all population differences would lie).
Wilcoxon Signed Rank test is the non parametric of the dependent sample T test (paired). Non parametric simply means that the data does not follow normal distribution. It is used to compare two sets of scores that come from the same participants.
An example is difference in alcoholic’s daily alcohol consumption before and after a 6 week Dialectical behavioral therapy programmed (i.e., your dependent variable would be "daily alcohol consumption", and your two related groups would be the ALCOHOL consumption values "before" and "after" the DBT programmed)
The Mann-Whitney U test is used to compare differences between two independent groups when the dependent variable is either ordinal or continuous, but not normally distributed.
For example, you could use the Mann-Whitney U test to understand whether attitudes towards pay discrimination, where attitudes are measured on an ordinal scale, differ based on gender (i.e., your dependent variable would be "attitudes towards pay discrimination" and your independent variable would be "gender", which has two groups: "male" and "female"). Alternately, you could use the Mann-Whitney U test to understand whether salaries, measured on a continuous scale, differed based on educational level (i.e., your dependent variable would be "salary" and your independent variable would be "educational level", which has two groups: "high school" and “university").
The main difference is that the Mann-Whitney U-test tests two independent samples (different subjects), whereas the Wilcox sign test tests two dependent (paired) samples(repeated measurements on same subjects)
F test and Bland Altman plot can be performed on EXCEL sheet. However, a statistical software such as SPSS may be required to perform MANN WHITNEY and WILCOXON SIGNED RANK test.
A step by step tutorial has been demonstrated in the video attached above.