A high z-score indicates an observation that is further away from the mean. This indicates that either the observation is less probable or that assumptions about the distribution are wrong.
z score = (test score - mean score)/SD z score = (87-81.1)/11.06z score = 5.9/11.06z score = .533You can use a z-score chart to calculate the probability from there.
A z-score of 0 means the value is the mean.
The z-score must be 1.87: the probability cannot have that value!
Z Score is (x-mu)/sigma. The Z-Score allows you to go to a standard normal distribution chart and to determine probabilities or numerical values.
A high z-score indicates an observation that is further away from the mean. This indicates that either the observation is less probable or that assumptions about the distribution are wrong.
The Z-score is just the score. The Z-test uses the Z-score to compare to the critical value. That is then used to establish if the null hypothesis is refused.
what is the z score for 0.75
z score = (test score - mean score)/SD z score = (87-81.1)/11.06z score = 5.9/11.06z score = .533You can use a z-score chart to calculate the probability from there.
Yes a Z score can be 5.
If the Z Score of a test is equal to zero then the raw score of the test is equal to the mean. Z Score = (Raw Score - Mean Score) / Standard Deviation
Find the Z score that correspond to P25
A z-score is a linear transformation. There is nothing to "prove".
Assume the z-score is relative to zero score. In simple terms, assume that we have 0 < z < z0, where z0 is the arbitrary value. Then, a negative z-score can be greater than a positive z-score (yes). How? Determine the probability of P(-2 < z < 0) and P(0 < z < 1). Then, by checking the z-value table, you should get: P(-2 < z < 0) ≈ 0.47725 P(0 < z < 1) ≈ 0.341345
Let z be positive so that -z is the negative z score for which you want the probability. Pr(Z < -z) = Pr(Z > z) = 1 - Pr(Z < z).
Z score of 0 is the mean of the distribution.
A z-score of 0 means the value is the mean.