The National Center for Health Statistics has estimated the life expectancy of males and females at birth over a multiple year period. The 15-year data sample of life expectancy is

summarized in the following table: We are interested in obtaining the linear relationship between year of birth (YEAR) and life expectancy (LE). Analysis has shown the life expectancy for males follows the relationship: LE = 0.143*YEAR-212.5 You are expected to obtain the life expectancy relationship for females over the same time period. You may use Excel to tabulate the summations, but not to calculate any of the parameters of the regression analysis directly. \text { a) Calculate } \boldsymbol{\Sigma} X_{\boldsymbol{i}} \text {. (You may calculate this table in Excel). } \text { b) Calculate } \bar{\Sigma} Y_{i} \text {. (You may calculate this table in Excel). } \text { c) Calculate } \bar{\Sigma} X_{i} X_{i} \text {. (You may calculate this table in Excel). } \text { d) Calculate } \sum Y_{i} Y_{i} \text {. (You may calculate this table in Excel). } \text { e) Calculate } \sum X_{i} Y_{i} \text {. (You may calculate this table in Excel). } Using the least squares approach, calculate the slope m and y-intercept b for the straight line which best fits the data in the table. You may NOT use Excel. Calculate the coefficient of correlation, r, for the line found in step f. You may NOT useExcel. plot both the male and female data found in the table along with the trend line evaluated in step f. You may present the plot using Excel output.