There are 1275 observations with values ranging from ~ -0.07 to mostly 0.08. I have 4 outliers that are over 0.8 (0.12, 0.12, 0.12 and 0.10). I want to convert this data into a 40-100 scaling system with a mean of 70 and a sd of 10-15. I also want around 5% of the scores to be over 90.
When I currently rescale it in r, I get a set of scores with:
mean: 62.07262 sd: 7.841568
I also only get 4 scores of over 90 due to the outliers. I tried changing the mean and sd of the scores set to 70 and 10 manually which predictably resulted in scores over 100 which I don't want. I also tried the Box-Cox transformation but that also didn't yield the results I wanted.
I would appreciate any methods to achieve the solution I want or if it is possible at all.