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z score = (test score - mean score)/SD z score = (87-81.1)/11.06
z score = 5.9/11.06
z score = .533


You can use a z-score chart to calculate the probability from there.

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15y ago

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Calculate a deviation score?

27


How do you calculate standard deviation with the help of z-score?

A z-score cannot help calculate standard deviation. In fact the very point of z-scores is to remove any contribution from the mean or standard deviation.


What is the z score of x equals 108?

You need the mean and standard deviation in order to calculate the z-score. Neither are given.


How do you calculate a priori probability when you know standard deviation and mean scores?

If it is possible to assume normality, simply convert the desired score to a z-score, and look up the probability for that.


Which is better a score of 92 on a test with a mean of 71 and a standard deviation of 15 or a score of 688 on a test with a mean of 493 and a standard deviation of 150?

score of 92


Why use the T score?

T-score is used when you don't have the population standard deviation and must use the sample standard deviation as a substitute.


How can you calculate z-score?

If a normally distributed random variable X has mean m and standard deviation s, then z = (X - m)/s


What will the sum of the deviation score always be?

zero


What happens to the standard score as the standard deviation increase?

The standardised score decreases.


When is a t test better than a z score?

When you don't have the population standard deviation, but do have the sample standard deviation. The Z score will be better to do as long as it is possible to do it.


A z score is most affected by?

standard deviation


How do you compute a z-score for the Beery VMI?

To compute a z-score for the Beery Visual-Motor Integration (VMI) test, first obtain the raw score from the test. Then, use the mean and standard deviation of the normative sample for the Beery VMI to calculate the z-score using the formula: ( z = \frac{(X - \mu)}{\sigma} ), where ( X ) is the raw score, ( \mu ) is the mean, and ( \sigma ) is the standard deviation. The resulting z-score indicates how many standard deviations the raw score is from the mean of the normative population.