Stats Exam 3 (T or F)
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
