z = 3
T-scores and z-scores measure the deviation from normal. The normal for T-score is 50 with standard deviation of 10. if the score on t-score is more than 50, it means that the person scored above normal (average), and vise versa. The normal for Z-score is 0. If Z-score is above 0, then it means that person scored above normal (average), and vise versa.
The z-score is 0.84. In the related link, look in the body of the table for .3 area (.2995 closest) and it yields the .84 z-score.
It is 0.017864
z = (x - μ) / σ is the formula where x is the raw score and z is the z-score. μ and σ are the mean and standard deviations and must be known numbers. Multiply both sides by σ zσ = x-μ Add μ to both sides μ + zσ = x x = μ + zσ You calculate the raw score x , given the z-score, μ and σ by using the above formula.
it means that the score is above the mean
A Z score of 300 is an extremely large number as the z scores very rarely fall above 4 or below -4. About 0 percent of the scores fall above a z score of 300.
z = 3
It is 0.1003
T-scores and z-scores measure the deviation from normal. The normal for T-score is 50 with standard deviation of 10. if the score on t-score is more than 50, it means that the person scored above normal (average), and vise versa. The normal for Z-score is 0. If Z-score is above 0, then it means that person scored above normal (average), and vise versa.
Pr(Z > 1.16) = 0.123
The z-score is 0.84. In the related link, look in the body of the table for .3 area (.2995 closest) and it yields the .84 z-score.
It is 0.017864
You can find this using a table of z scores.Z = (x - mu) / sZ = (109 - 100) /15 = 9/15 = 3/5 = .6You want the percentage of students having a z score above .6.p = 1 - .7257 = .2743.2743 * 1800 = 493 students with a score above 109
It is 1.6 standard deviations above the mean.
z = (x - μ) / σ is the formula where x is the raw score and z is the z-score. μ and σ are the mean and standard deviations and must be known numbers. Multiply both sides by σ zσ = x-μ Add μ to both sides μ + zσ = x x = μ + zσ You calculate the raw score x , given the z-score, μ and σ by using the above formula.
A z score is a value that is used to indicate the distance of a certain number from the mean of a normally distributed data set. A z score of -1.0 means that the number is one standard deviation below the mean. A z score of +1.0 means that the number is one standard deviation above the mean. Z scores normally range from -4.0 to +4.0. Hope this helps! =)