1. The following is an image of a Cartesian diagram. y (3, 4) (5, 4) (3, 3) (6, 3) (3, 2) 2. (1, 1) X From the picture above, determine the estimation result of the Linear Regression Equation.
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- 4. Write a Julia function to calculate CV and GCV in the case of smoothing by local linear regression.The annual expenditure for cell phones varies by the age of an individual. The average annual expenditure E(a) (in $) for individuals of age a (in years) is given below:a: 20, 30, 40, 50, 60, 70E(a): 502, 658, 649, 627, 476, 2131. Use quadratic regression to find the model that best represents the data.2. At what age is the yearly expenditure for cell phones the greatest? Round the answer to the nearest year. YOU MUST SHOW THE WORK FOR THIS PART!Þata on the relationship between plant age and dry matter in the stalk are given in the Table. X (Age) 4 6 8 10 12 14 16 18 Y (Dry matter, %) 24 28 35 48 44 49 51 | 51 i) Express the relationship between the exhausted age and dry matter level with the regression equation (Ý = aX + b). ii) Using the obtained equation, estimate what the dry matter% of plants with ii) a age of 22 weeks will be. iii) By drawing the skater diagram, find the correlation coefficient and interpret the found values. iii)
- 1) create a line in DESMOS with the linear regression equation: y1 ~ mx1 + b 2) create a second line with quadratic regression: y1 ~ ax1^2 + bx + c After looking at the regression in DESMOS, is the data LINEAR or QUADRATIC?Consider the points in the plane: (1,2) (2,3) (3,5) (4,4) (5,7) (7,8) (i) Compute the correlation coefficient. (ii) Compute the equation for the regression line.Solve b
- c) Give the expression of R˜^2 in terms of R^2 , and justify your answer.3A weight-loss clinic wants to use regression analysis to build a model for weight loss of a client (measured in pounds), Two variables thought to affect weight loss are client's length of time on the weight-loss program and time of session These variables are described below: Y-BO+B1'X+82'D 83'X'D+E Y-Weight loss (in pounds) X- Length of time in weight-loss program (in months) D-1 if morning session. O if not in terms of the Bs in the model, what is the difference between the weight loss of an individual who has spent 3 months in the program when attending the morning session, and an individual who has spent 2 months in the program when attending the evening session? OB1+83 OB1+82-83 OB1+82+283 O81+82+383
- ***PLEASE INCLUDE EXCEL OUTPUT WITH YOUR RESPONSE4. Our R² implies that lots of stuff, other than health, also affects doctor visits. One such thing is a person's insurance status. The data file includes a third variable that records whether the person had health insurance during 2019. Estimation a regression of the form y = Bo + B₁x1 + B₂x₂ where x₁ is the health status variable from above, but now x₂ records whether the person had insurance. a) Interpret the estimate of B₁ in words. b) Interpret the estimate of B₂ in words. c) Forecast a person's number of doctor visits in 2019 if he/she was in excellent health, but did not have insurance. d) Forecast a person's number of doctor visits in 2019 if he/she was in poor health, and did have insurance. e) The R² for this regression isThe owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x,) and newspaper advertising (x,). The estimated regression equation was ý = 82.3 + 2.29x, + 1.90x2. The computer solution, based on a sample of eight weeks, provided SST = 25.1 and SSR = 23.415. (a) Compute and interpret R? and R 2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is 653 x . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (b) When television advertising was the only independent variable, R2 = 0.653 and R,2 = 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis (is preferred since both R2 and R.2 show an increased v v…
