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I'm doing a regression analysis which involves 4 independent variables (IV). I performed a Shapiro-Wilk test to test the normality of of each of the IVs and it turned out that the the test showed a value less than 0.05 (which means the data is not normally distributed).

So the question is how do i make my data to follow a normal distribution. Because all parametric tests are based on the assumption that the data is normally distributed.

My data set consist of 26 records (n=26). The dependent variable is House Price Index. While the IV is Gross Domestic Product, Population, Lending Rates and Gross National Income.

Therefore I'm trying to come up with a regression model with these variables. But im facing the normality problem in the IV and DV data distributions.

Thank you.

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    $\begingroup$ It is not true that your data has to be always and exactly normally distributed for parametric tests, see: stats.stackexchange.com/questions/2492/… and if you really need to transform you data, Box-Cox is the simple and commonly used approach en.wikipedia.org/wiki/… But to provide the precise answer you have to tell what is your data and what do you want to do with it? $\endgroup$ – Tim Apr 28 '15 at 8:06
  • $\begingroup$ @Tim Thank you Tim. I have added more details to my question. $\endgroup$ – Raam Apr 28 '15 at 10:06
  • $\begingroup$ With such a small sample the sample size should be a greater concern to you than normality. $\endgroup$ – Tim Apr 28 '15 at 10:12
  • $\begingroup$ @Tim Agreed Tim. I would want to increase the number of records but the available (published) data is only that much. $\endgroup$ – Raam Apr 28 '15 at 10:18
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    $\begingroup$ Please explain what form of "regression analysis" you are using that requires the IVs to have (approximately) normal distributions. $\endgroup$ – whuber Apr 28 '15 at 15:27

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