There is insufficient information for us to answer this question. Please edit the question to include more context or relevant information. It would also be useful to develop the habit of checking your questions for completeness before posting them.Calculation of a z-score requires information on the mean and standard error of the variable for which the z-score is to be calculated.
It so unlikely as not to warrant even thinking about. A z-score of 4.89 implies a probability of around one in a million.
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
Yes a Z score can be 5.
Find the Z score that correspond to P25
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
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.
The z-score must be 1.87: the probability cannot have that value!