Hi, for a university project I currently have to analyze a dataset inherent to a cluster of stars, in which the two main variables are luminosity and temperature of each star.
The main goal is to validate the normality hypothesis in both variables (usually I go with >qqnorm() + >qqline() + >shapiro.test(), and based on the p-values I decide wether or not continuing the analysis with parametric or non-parametric tests).
Do I have to perform a transformation on each variable before testing them for normality? I was thinking about doing an exponential transformation but I'm not sure if that's a good move.
The main goal is to validate the normality hypothesis in both variables (usually I go with >qqnorm() + >qqline() + >shapiro.test(), and based on the p-values I decide wether or not continuing the analysis with parametric or non-parametric tests).
Do I have to perform a transformation on each variable before testing them for normality? I was thinking about doing an exponential transformation but I'm not sure if that's a good move.