Stats Exam 3 (T or F)

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SS measures the sum of all scores

false

Subtracting 5 points from every score in a population will decrease the population variance

false

a decision to reject the null hypothesis means you have demonstrated that the treatment has no effect

false

a small sample will result in more power than a large sample

false

an unusually small value (close to zero) for the z-score statistic is evidence that the null hypothesis should be rejected

false

as sample size decreases the Z score increases

false

as sample size decreases the expected value of the mean decreases

false

as sample size decreases the standard error of the mean decreases

false

as sample size increases the expected value of the mean decreases

false

as the alpha level gets smaller, critical Z scores get smaller

false

as the difference between the sample and population means decreases the Z score will tend to increase

false

as the difference between the sample and population means increases the Z score will tend to decrease

false

as the population standard deviation decreases the standard error of the mean will increase

false

as the population standard deviation increases the standard error of the mean would be expected to decrease

false

decreasing sample size will tend to increase the Z score

false

degrees of freedom equals the sample size

false

increasing sample size will tend to decrease the Z score

false

sample means will NOT vary if all the samples are the same size and all samples are selected from the same population

false

sample means will not vary from sample to sample even if all the samples are the same size and all samples are selected from the same population

false

samples tend to overestimate their populations with respect to variability

false

standard deviation is the mean of the squared deviation scores

false

the alternative hypothesis states there is no change, no difference and that the IV has no effect

false

the standard deviation summarizes squared distances from the mean

false

the sum of X (X) is to the mean as the sums of squares (SS) is to the standard deviation

false

the value you obtain for SS will be different depending on whether the set of scores is a sample or a population

false

SS is equivalent to total squared error

true

a large sample will result in more power than a small sample

true

an unusually large value (far from zero) for the z-score statistic is evidence that the null hypothesis should be rejected

true

as sample size increases the standard error of the mean decreases

true

as the alpha level gets smaller the size of the critical region also gets smaller

true

as the difference between the sample and population means increases the Z score will tend to increase

true

as the population standard deviation decreases the standard error of the mean would be expected to decrease

true

as the population standard deviation increases the standard error of the mean will increase

true

as the population variability increases the standard error of the mean would be expected to increase

true

as variability increases the Z score will tend to decrease

true

as variability increases the Z score will tend to decrease.

true

in many journals including those following APA style the symbol SD is used for the sample standard deviation

true

increasing sample size will tend to increase the Z score

true

sample means will vary from sample to sample even if all the samples are the same size and all samples are selected from the same population

true

the expected value of the mean is equal to the population mean

true

the null hypothesis states there is no change, no difference and that the IV has no effect

true

the standard deviation is the typical distance from the mean

true

the sum of X (X) is to the mean as the sums of squares (SS) is to variance

true

variance is the average of the squared distances from the mean

true

variance is the mean of the squared deviation scores

true


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