Common Statistical Tests

There are various statistical tests in Data Analysis, following are the tests and their use:-
1. Correlation -> This test looks at the association between variables
2. Pearson Correlation -> It tests the strength of the association between two continuous variables
3. Spearman correlation -> It tests the strength of association between two ordinal variables
4. Chi-Square -> It tests for the strength between two categorical variables

Comparison of Means – The below tests looks for the difference between the means of variables

1. Paired T-test ->Test for difference between two relatable variables
2. Independent T-Test -> Test for difference between two related variables
3. ANOVA -> It stands for Analysis of Variance. It is a statistical method used to test differences between two or more means.

Regression – It assess if change in one variable predicts change in another variable

1. Simple Regression – Tests how change in the predictor variable predicts the level of change in the outcome variable
2. Multiple Regression – Tests how change in the combination of two or more variables predict the level of change in the outcome variable

Non-Parametric – These tests are used when the data does not meet assumptions required for parametric tests

1. Wilcoxon rank-sum test -> Tests for difference between two independent variables, takes into account magnitude and direction of difference

2. Wilcoxon sign-rank test -> Test for difference between two related variables, takes into account magnitude and direction of difference

3. Sign test -> Tests if two related variables are different – ignores magnitude of change, only takes into account direction

We will have a separated blog for all the tests separately. Till then google.

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