Which of the following is an assumption of the independent-samples t test, but not an assumption of the one-sample t test?
a. random selection from the population or populations of interest.
b. having a dependent variable that is measured as a scale variable.
c. homogeneity of variance .
d. all of the assumptions above apply to both one-sample and independent-samples t tests.

B & C

Step-by-step explanation:

• By definition in statistics, an Independent-samples t-test is one used to compare the means of two groups. Meanwhile,

a one-sample t-test is used to compare the mean of a single group against that of a known mean.

• The assumptions for an Independent-samples t-test are;

- Assumption of Independence where we represent the independent variable with the use of two independent and categorical groups.

- Assumption of normality whereby the dependent variable must be approximately normally distributed. Also the dependent variable must be measured as a scale variable.

- Assumption of Homogeneity of Variance whereby the variances of the dependent variable must not be equal to each other.

• The assumptions for one sample t-test are;

- The data must be independent.

- The sample size must be randomly selected.

- The data sample must be approximately normally distributed.

Looking at the assumptions for both tests above, it is clear that the only one that applies to the Independent-samples t-test but not the one sample t-test is assuming homogeneity of variance and that the dependent variable must be measured as a scale variable. .

Thus, options B and C are correct.

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0.84 dang lotta people are looking for this lol or if you round up its 1 but the overall answer to that is 0.84

step-by-step explanation:

ans789

step-by-step explanation: