I have a random variable and many observations of that variable. The random variable is not normally distributed; its distribution is unknown.
However, to analyze this variable and construct a time series model, I need to force this variable to have a normal distribution. I was given this suggestion:
- Take an observation of random variable X=x and compute its CDF value 0 < F(x) < 1
- Take this value F(x) and plug it into the Inverse Normal CDF, and this will return a Z-score corresponding the the observation X=x
Can I use this transformation to convert my data from an unknown distribution to the normal distribution?