c) With reference to the table above, specify the coefficient of determination and interpret it. d) Test the null hypothesis that the true intercept (_cons for the regression model) is zero. e) Predict protein S when protein C is 100 iu/dl.
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- Using the following table, I'm not sure how to answer these questions: a) Find the estimated regression equation of price on the percentage of space containing ads. y^ = +( )x b) Predict the price of a magazine with 47% of is space containing ads. rounding to 3 decimal places c) Estimate the price of a magazine with 98% of its space containing ads. Runded to 3 decimal placesThe 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 ŷ = 82.3 + 2.23x, + 1.40x2. The computer solution, based on a sample of eight weeks, provided SST = 25.8 and SSR = 23.395. (a) Compute and interpret R2 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 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 --Select--- v preferred since both R2 and R show ---Select- v percentage…Consider a linear spline with 16 knots. How many regression coefficients do you estimate when running a linear regression model with that spline?
- Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is: kids; = Bo + B1educ; + uż. 1. What are the parameters in the model? 2. What kinds of factors are contained in u? Are these likely to be cor- related with level of education? 3. Will a simple regression analysis uncover the ceteris paribus effect of education on fertility? Explain.The large national bank charges local companies for using their services. A bank official reported the results of a regression analysi designed to predict the bank's charges (Y), measured in RM per month for services rendered to local companies. One independent variable used to predict service charge to a company is the the company's sales revenue (X), measured in millions of RM. Data for 21 companies who use the bank's services were used to fit the model. The results of the simple linear regression are provided below. Based on results below, a 95% confident interval for B is (15,30). Interpret the interval. * ŷ = -2,700 + 20X Sxy = 65, two – tailed p – value = 0.034 (for testing B We are 95% confident that the sales revenue (X) will increase between RM15 and RM30 million for every RM1 increase in service charge (Y). We are 95% confident that the mean service charge will fall between RM15 and RM30 per month. We are 95% confident that the average service charge (Y) will increase between…A particular article presented data on y = tar content (grains/100 ft³) of a gas stream as a function of x₁ = rotor speed (rev/min) and x₂ = gas inlet temperature (°F). The following regression model using X₁, X2, X3 = ×₂² and ×4 = X₁X₂ was suggested. (mean y value) = 86.5 – 0.121x₁ +5.07x2 - 0.0706x3 + 0.001x4 (a) According to this model, what is the mean y value (in grains/100 ft³) if x₁ = 3,400 and x₂ = 55. grains/100 ft³ (b) For this particular model, does it make sense to interpret the value of ₂ as the average change in tar content associated with a 1-degree increase in gas inlet temperature when rotor speed is held constant? Explain. Yes, since there are no other terms involving X2. O Yes, since there are other terms involving X₂. ● No, since there are other terms involving X2. O No, since there are no other terms involving X2.
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- Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)The 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 ŷ = 82.1 + 2.23x, + 1.70x2. The computer solution, based on a sample of eight weeks, provided SST = 25.1 and SSR = 23.345. (a) Compute and interpret R2 and R_2. (Round your answers to three decimal places.) . Adjusting for the number of independent variables in the model, the The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation isA study was conducted in California to investigate the relationship between house size (x in square feet) and house price (y in thousands of dollars). The least-square regression line is given below y= 263.5 + 0.174x R2 = 0.728 a) Interpret the slope of the given regression line b) find the predicted house price for a house size of 120 square feet c) if the actual house price was $449.5 thousand dollars for a house size of 1200 square feet, calculate the residual of the home d) find the correlation coefficient. Round to 3 decimal places