The data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) to (c) below. E Click the icon to view the data table. or (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for females. Find the least-squares regression line for males. Data for licensed drivers by age and gender. (Round the slope to three decimal places and round the constan in Number of Number of n Number of Male Fatal Licensed Drivers Crashes Number of Female Fatal Licensed Drivers (000s) Crashes Age (000s) (Males) (Females) < 16 12 227 12 77 16-20 6,424 5,180 6,139 2,113 21-24 6,970 5,016 6,816 1,531 25-34 18,068 8,575 17,664 2,780 35-44 20,406 7,990 20,022 2,742 45-54 19,898 7,121 19,984 2,285 me 55-64 14,350 4,527 14,441 1,514 riv 65-74 8,194 2,274 8,370 5,375 938 > 74 4,803 2,022 973 Enter your answer in the edit fields and then click Check Ans Print Done 9 parts remaining

The data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) through (c) below. Click the icon to view the data table. ..... (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for females. Find the least-squares regression line for males. y =x+O %D/ (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) Find the least-squares regression line for females. y = ý =x+O %3D (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) (b) Interpret the slope of the least-squares regression line for each gender, if appropriate. How might an insurance company use this information? What is the correct interpretation of the…

The data below are the temperatures on randomly chosen days during the summer and the number of employee absences at a local company on those days.  Temperature:           Number of absences                               72                                3 85                               7 91                                10 90                                10 88                                 8                           98                                 15 75                                 4 100                               15 80                                 5 (a) Find the least square regression line.  Round slope and y-intercept nearest hundredth. (b) Predict the number of absences when temperature is 88.  (c) Find the residual when temperature is 98.   Analyze the result.   (b) Test the claim, at the α = 0.05 level of significance, that a linear relation exists between the temperature and number of absences.  Apply classical approach and p-value approach. (c) Find 95 %…

The manager of a car dealership wants to predict the relationship between number of sales persons and the number of cars sold. He collects some data to develop a regression model, which is given below         Week Number of cars sold Number of salespersons 1 80 6 2 90 8 3 48 4 4 55 5 5 60 7 6 75 9 7 100 11 8 70 6 9 65 7 10 98 10   (i) Run a regression analysis which explains the number of cars sold in terms of number of salespersons, and estimate the regression line                                                                              (ii) Interpret the regression coefficient, and determine the significance of the regression coefficient                                                                                                                                             (iii) Interpret the overall model fit…