1. In a one-sample t-test

A. The test, because only one sample is used, can only be one-tailed

B. The population standard deviation is available and as a result, the standard deviation is not divided by the square root of the sample size

C. The sample standard error of the mean is used since the population mean is being compared to a sample mean

D. The null hypothesis requires that the sample mean is always compared to 0

2. A need for using a likelihood estimate when determining the best model for a logistic regression is

A. The x axis is undefined

B. The residual values can't be computed

C. The x variable values are always equal to 0

D. The degrees of freedom in a logistic regression equals 0

3. The standard error of the mean

A. Is the value obtained when subtracting a sample mean from the population mean

B. Appears in the bottom (denominator) of a t-test formula

C. Appears in the top (numerator) of a t-test formula

D. Is the value obtained when subtracting a single observation from the population mean

4. In a two-sample, independent t-test

A. If the sample means of the two samples are different, the test will always be statistically significant

B. Because there are two samples, the error term (the denominator of the t-test ratio) is two times the value of the larger standard deviation

C. The standard error involves the standard deviations from both samples

D. Because there are two samples the standard error of the mean that is used is the larger of the two standard errors of the mean

5. A z-score calculated using one sample set of data

A. is likely to be a larger value than a t-score

B. will always only be a positive number

C. represents a ratio of difference of means divided by an error term

D. can only be between 1 standard deviation above and below the mean