Final answer:
The statement is true; standardization of a distribution results in z-scores that have a mean of 0 and a standard deviation of 1, forming the standard normal distribution.
Step-by-step explanation:
The statement is true. Regardless of the values for the original distribution, after standardization the mean for the z-score is always zero, and the standard deviation is always 1. Standardization is the process of converting individual scores in a distribution to z-scores, which allows us to create a new distribution called the standard normal distribution (Z ~ N(0, 1)). This process re-scales the data so that the mean of the z-scores becomes 0 and the standard deviation becomes 1, facilitating comparison across different datasets. The calculation of a z-score is z = (x - μ) / σ, where x is the raw score, μ is the population mean, and σ is the population standard deviation.