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- Given that the systolic blood pressure in the right arm is 90 mm Hg, the best systolic blood pressure in the left arm is how many mm Hg?Select the appropriate interpretation for the slope of the linear regression equation below. Y (Dependent Variable) = Grade Point Average X (Independent Variable) = Average number of hours spent using electronic devices for entertainment purposes yhat = 4 - 0.125*X A. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will increase on average by 0.125 points B. For every 1 GPA gained obtained by a student then on average that person will have watched 0.125 hours fewer of entertainment on electronic devices per week C. For every 1 GPA point lost by a student then on average that person will have watched 0.125 hours more of entertainment on electronic devices per week D. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will decrease on average by 0.125 pointsData from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
- A researcher is interested in finding out the factors which determined the yearly spending on family outings last year (Y, measured in dollars). She compiles data on the number of members in a family (X1), the annual income of the family (X2), and the number of times the family went out on an outing in the last year (X3). She collects data from 196 families and estimates the following regression: Y=120.45+1.54X1+2.12X2+2.12X3. Suppose β1, β2, β3, denote the population slope coefficients of X1, X2, and X3, respectively. The researcher wants to check if neither X1 nor X2 have a significant effect on Y or at least one of them has a significant effect, keeping X3 constant. She calculates the value of the F-statistic for the test with the two restrictions (H0: β1=0, β2=0 vs. H1: β1≠0 and/or β2≠0) to be 3.00. The p-value for the test will be enter your response here?It has been hypothesized that overall academic success for first-year college students as measured by grade point average (GPA) is a function of IQ scores = X1, and hours spent studying each week = X2. Suppose the regression equation is: Y = -5.7 + 0.02X1 +0.5X2 1) What is the predicted GPA for a student with an IQ of 100 and 40 hours spent studying per week? 2)Will the independent variables be endogenous? State what it means by endogenous, and explain why that will be the case. 3) If you have a choice to change the variables or add/drop variables, what would be your set of independent variables, and explain why you chose those variables.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 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…
- A particular article used a multiple regression model to relate y = yield of hops to x, = average temperature (°C) between date of coming into hop and date of picking and x, = average percentage of sunshine during the same period. The model equation proposed is the following. y = 415.11 – 6.6x1 – 4.50x2 +e (a) Suppose that this equation describes the actual relationship. What mean yield corresponds to a temperature of 20 and a sunshine percentage of 40? (b) What is the mean yield when the average temperature and average percentage of sunshine are 19 and 44, respectively?A particular article used a multiple regression model to relate y = yield of hops to x₁ = mean temperature (°C) between date of coming into hop and date of picking and x₂ = mean percentage of sunshine during the same period. The model equation proposed is the following. y = 415.116.6x₁4.50x2+e (a) Suppose that this equation does indeed describe the true relationship. What mean yield corresponds to a temperature of 20 and a sunshine percentage of 39? (b) What is the mean yield when the mean temperature and percentage of sunshine are 19.1 and 42, respectively? You may need to use the appropriate table in Appendix A to answer this question.The following table gives the amount spent on cellular service. Date Cellular service revenue(in billions) 2011 1.01 2012 1.05 2013 1.09 2014 1.11 Plot the data points. (Let tbe the number of years since 2011 and C the amount of cellular service revenue, in billions of dollars.) CORRECT (b) Find the equation of the regression line. (Let t be the number of years since 2011 and C the amount of cellular service revenue, in billions of dollars. Round the regression line parameters to three decimal places.) C(t) = C(t) = 0.034t+1.014 CORRECT Add its graph to the plotted data. CORRECT (c) In 2015, $1.14 trillion was spent on cellular service. If you had been a financial strategist in 2014 with only the data in the table above available, what would have been your prediction for the amount spent on cellular service in 2015? (Round your answer to two decimal places.) billion dollars CORRECT…
- Suppose you use regression topredict the height of a womanscurrent boyfriend by using her ownheight as the explanatory variable.Height was measured in feet from asample of 100 womenundergraduates, and their boyfriends,at Dalhousie University. Now, supposethat the height of both the womenand the men are converted tocentimeters. The impact of thisconversion on the slope is:Define both x and y in all problems. x is the cause, and y is the effect. This is the most important step when doing linear regression, otherwise, all the remanding parts will be wrong.
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