Greetings,
I am testing to see if linear relationships exist between my x and y variables.
I conducted various diagnoses in R to test for normality of the x variable data
by using qqnorm, qqline and histograms that show the distribution of the data.
If the data is shown to be normally distributed in either normal quantile plots
or in the histograms (i.e. a bell curve-shaped distribution), I would assume
normality and apply the linear regression model, using "lm". However, in some
cases, my distributions do not satisfy the normality criteria, and so I feel
that using the linear regression model, in those cases, would not be
appropriate. For that reason, would you be able to suggest an alternate test to
the linear regression model in R? Maybe a non-parametric counterpart to it?
Thank you, and any help would be greatly appreciated!
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