I am having trouble figuring out these five practice problem questions.

What is a confounding factor? a. A factor that multiplies the strength of the relationship by the average of that factor. b. An outside factor that impacts the variable(s) of study. c. Another name for the dependent variable in a regression equation. d. An extreme outlier in the data that impacts the correlation coefficient. Which of the following statements are true about normal distributions? Select all that apply. a. Normal distributions are symmetrical b. The mean, median and mode are all equal c. The total area under the curve depends on what the mean is d. The line always extends from 0 to 100Explain the two things you should be cautious about when making predictions with linear regression. True or False: Linear regression can include more than one independent variable. What is the formula for a residual in linear regression? What does it represent