4 A research team conducted a longitudinal study of participants between 45 and 50 years of age. They measured each participant's average daily caloric consumption at age 45. They also measured body mass index (BMI) at age 50. BM] is a measure of obesity with higher BMI indicating more obesity. The team collected data on n = 812 participants. The average BM] at age 50 was 23.2, with an observed standard deviation of 18 (the divisor in the underlying variance calculation was 1': 1}. The average daily caloric consumption age 45 was 3,260, with an observed standard deviation of 242.3 (the divisor in the underlying variance calculation was It 1 ). The Pearson product moment correlation coefficient between the We variables was 0.38. The research team seeks to estimate the regression of BMI at age 50 on the participant's daiiy caloric consumption lifestyle at age 45. a. Complete the analysis of variance table for the regression of ENE at age 50 on the participant's daily caloric consumption at age 45. Test the null hypothesis that the slope of this regression is zero at levels of signicance 0.10, 0.05, and 0.01. 25 points. b. Find the estimated regression of BM! at age 50 on the participant's daily calorie consumption at age 45. Find the 99% condence interval for the slope in this equation. This part is worth 25 points. c. Use the least-squares equation to estimate the BMI at age 50 for participants whose daily caloric consumption at age 45 was 4,000 units. What is the 99% condence interval for BMI at age 50 for participants whose daily caloric consumption at age 45 was 4,000 units. 20 pts