We would like to study the relationship between the STAT 302 students' final exam scores and their second exam scores. Data from past semester are used as a sample to fit a least-squared regression line to predict (or estimate) the individual or mean final exam score for a given exam 2 score. Click on Read Output to read the JMP regression output and answer the questions below. (a) The mean final exam score is (Round to 1 decimal place) (b) The correlation between final and exam 2 is (Round to 3 decimal places) (c) The exam 2 scores account for percent of variations in final exam scores. (Round to 1 decimal place) (d) percent of the variations in final exam scores remains unexplained and is considered as errors. (Round to 1 decimal place) (e) The point estimate for the equal variance σ2 in this regression model is . (f) For students who has exam 2 score of 75, with 95% confidence, we estimate their mean final exam score is between and . (Round to 2 decimal places) (g) A student's exam 2 score is 75, with 95% confidence, we estimate his (or her) final exam score is between and . (Round to 2 decimal places) (h) The residual plot indicates (Select all that apply.) The residual plot validates the assumption of equal variance in this model. The distribution of residual is approximately normal. The distribution of residual is skew. The residual plot has an obvious non-linear pattern