TRUE OR FALSE:

31. Since a one-sample t-test only compares an observed mean to an expected value, you won't likely need to visualize it in a graph.

32. Sometimes it's not clear which is the independent variable and which is the dependent, even if you think there may be a cause-and-effect relationship.

33. The coefficient of determination, or r2, expresses the strength of the relationship between the X and Y variables.

34. One-sample t test is considered statistically significant only when the standard error computed in descriptive statistics for the sample population is quite large.

35. If we reject the null hypothesis on a one-sample t-test, it means that the sample mean is very close in value to the population mean.

36. In biology, there is no difference in the interpretation of correlation and regression.

37. All other things being equal, the higher the value of the computed t-test statistic, the smaller the distance between the sample mean and the expected population mean.

38. A paired t-test just looks at the differences, so if two sets of measurements are paired with each other, the paired t-test will be more powerful than a two-sample t-test.

39. If your data is severely non-normal, with different data distributions and a sample size of (n<50), the two-sample t-test can still give accurate results.

40. In ordinary least-squares regression, the "best" fit is defined as the line that minimizes the squared vertical distances between the data points and the line.