Data Normality Test in Research || Convert Non-Normal Data into Normal Data

In Normality Test, the hypothesises are:

H0: The data is normally distributed.

H1: The data is not normally distributed.

If low p-value (less than 0.05): Rejecting the null hypothesis = Data significantly deviates from a normal distribution = Data does not follow a normal distribution.

If high p-value (greater than 0.05): Do not reject the null hypothesis = Data to be normally distributed.

Comment: If the data is not normally distributed, parameters, such as means, variances, and regression coefficients, may be biased or inaccurate, affecting the validity of the conclusions.

From this tutorial, you will learn how to test the normality of data. It also explains how to transform non-normal data into normal data if the normality test indicates that the data is not normally distributed.


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