Making use of statistics is not just a choice

It’s a necessity in today’s competitive landscape. By leveraging statistical methodologies, businesses can unlock a world of possibilities, transforming raw data into actionable insights that drive success.

Type of Test Use
Pearson CorrelationTests for the strength of the association between two continuous variables
Spearman CorrelationTests for the strength of the association between two ordinal variables (does not rely on the assumption of normally distributed data)
Chi-SquareTests for the strength of the association between two categorical variables
Paired T-TestTests for the difference between two variables from the same population (e.g., a pre-test and post-test score)
Independent T-TestTests for the difference between the same variable from different populations (e.g., comparing males to females)
ANOVATests for the difference between group means after any other variance in the outcome variable is accounted for (e.g., controlling for age, or pain score)
Simple RegressionTests how the change in the predictor variable predicts the level of change in the outcome variable
Multiple RegressionTests how changes in the combination of two or more predictor Variables redict the level of change in the outcome variables
Wilcoxon Rank-Sum TestTests for the difference between two independent variables; takes into account magnitude and direction of difference
Wilcoxon Sign-Rank TestTests for the difference between two related variables; takes into account the magnitude and direction of difference
Sign TestTests if two related variables are different; ignores the magnitude of change—only takes into account direction