no 33.

Upper 95% Lower 95.0% Upper 95.0% -15.03565924 134067E-09 -17.646977 -13.212933 -17.646977 -13.212933 10 1.026224052 Hours playing computer games 0.60690583 0.031012382 19.56979064 0.00000000 0.53990765 0.67390401 0.53990765 0.67390401 1. In this regression model, the obesity of the Children is the (independent/dependent) variable (x/ y) and the Hours playing computer games is the (independent/dependent) variable (x/ y) 2. Determine the equation of the regression line (Write the values to 4 decimal places - including the sign (+ or -) y = * hours Playing computer games 3. Testing the slope of the regression line: p-value of the hours of playing computer games is report p-value to 4 decimal places; indicating there is a relationship between the hours of playing computer games and Childhood obesity. 6. The coefficient of determination is ; Provide an explanation of the coefficient of determination- 7. All other variables are constant, the addition of a one hour increase in playing computer games will result in a predicted increase of provide the answer to 4 decimal places) kg in overweight.( 9. So, if a Child plays 15 hours of computer games; the predicted overweight of the child is the answer to 4 decimal places) Kgs (Consider all values of the 4 decimal places and provide4 pts Question 32 A health care provider wanted to test the link between childhood obesity and the hours playing computer games per week. She took a sample of 15 8-year-old children. The number of kgs a child was overweight was recorded, along with the number of hours of computer games played per week. The Summary output below is to predict the number of kgs a child may be overweight depending on the number of hours playing computer games. SUMMARY OUTPUT Regression Statistics Multiple R 0.983447907 R Square 0.967169786 Adjusted R Square 0.964644385 Standard Error 0.845525936 Observations 15 ANOVA df SS MS F Significance F Regression 273.7954499 273.7954499 382.9767055 4.9966E-11 Residual 9.293883408 0.714914108 Total 283.0893333 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 15.42995516 1026224052 -15.03565924 134067E-09 -17.646977 13.212933 -17.646977 -13.212933 Hours playing computer games 0.60690583 0.031012382 19.56979064 0.00000000 0.53990765 0.67390401 0.53990765 0.67390401 1. In this regression model, the obesity of the Children is the (independent/dependent) variable (x/ y) and the Hours playing computer games is the (independent/dependent) variable (x/ y) LEGION ESC F2 FS a3 pts Question 33 For a sample of 8 employees, a personnel director has collected the following data on ownership of company shares versus years with the firm. A regression analysis has been performed for the two variables. Regression Statistics Multiple R 0.8486 R Square 0.7201 Adjusted R Square 0.6734 Standard Error 91.4789 Observations Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 44.3140 108.5087 0.4084 0.6972 -221.1973 309.8252 -221.1973 309.8252 x [Years) 38.7558 9.8644 3.9288 0.0077 14.6184 62.8932 14.6184 62.8932 Based on the regression output produced by Excel for the above data, answer the following question: Predict the number of shares that Cristiano has in the company if he has stayed with the firm for 11 years