Answer:
Mean of 0 and a standard deviation of 1.
Step-by-step explanation:
To transform the entire population into z-scores, one would need to normalize/standardize the scores.
The standardized score for any value is the value minus the mean then divided by the standard deviation.
Given mathematically as
z = (x - μ)/σ
The normal distribution shows how much a set of data points spread out around the mean.
A z-score is basically expressing how many standard deviations away from the mean is a particular data point.
z-score for the mean = (μ - μ)/σ = (60 - 60)/8 = 0
And any variable that is one standard deviation away from the mean will have a z-score of 1.
For example, 68 is one standard deviation away from the mean.
z-score for 68
z = (x - μ)/σ = (68 - 60)/8 = 1.
It is evident that normal distribution, when converted to z-scores has a mean of 0 and a standard deviation of 1.
The distribution of z-scores will have a mean of 60 and a standard deviation of 8/√number of samples.
Z score is used to determine by how many standard deviations the raw score is above or below the mean. It is given by:
z = (x - μ)/σ
Where x is the raw score, μ is the mean and σ is the standard deviation
Given that μ = 60 and σ = 8,
The distribution of z-scores will have a mean of 60 and a standard deviation of 8/√number of samples.
Find out more on z score at: https://brainly.com/question/25638875
