I am having quite a few problems with transforming a set of data with values between -1 and 0, as I need to normalise them.
I tried to use the following formulae:
But both don't seem to work... As the p-value is always below 0.05 using the Shapiro-Wilk test.
Can I transform the data using the log[(𝑥−min(𝑥))/(max(𝑥)−min(𝑥))] formula? Is this appropriate? Thanks xx
CLARIFICATION: Sorry guys, I am quite new to these things, I thought "normalise" meant making sure that a set of data was normally distributed. I have a set of data and I have to check to see whether they are normally distributed - and to see that, I was told that I have to use the Shapiro-Wilk test, which must be above 0.05, a histogram, and a Q-Q graph (I am using SPSS). But the data that I have comprises all negative values, and when I checked they were not normally distributed. On the Internet, I read that I have to log-transform my data, but since they're all negative values, I tried the two options above in my original post - plus log(x+1) yesterday evening. But nothing seems to work. My question was whether I could use the following formula log[(𝑥−min(𝑥))/(max(𝑥)−min(𝑥)) to transform my data and achieve normal distribution? Because I can't find anything else on the Internet on that... Or if there was anything else I could try?