Answer:
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.
Read more here; brainly.com/question/13477293
