escYou may need to use the appropriate technology to answer this question.The following is part of the results of a regression analysis involving sales (y in millions of dollars), advertising expenditures (x, in thousands of dollars), and number of salespeople (x₂) for a corporation. The regressionwas performed on a sample of 10 observations.ConstantX1x2Ho:55°FHeavy sleet(a) Write the regression equation.HaCoefficients-11.320ŷ = -11.320+0.788x1 +0.151x20.78820.151=Standard Error(b) Interpret the coefficients of the estimated regression equation found in part (a). (Give your answers in dollars.)As advertising increases by 1 unit ($1,000), sales are expected to increase by $ 788to increase by $ 151X when advertising is held constant.(c) At a = 0.05, test for the significance of the coefficient of advertising.State the null and alternative hypotheses. (Enter != for # as needed.)B₁ = 0B₁!=0Find the value of the test statistic. (Round your answer to two decimal places.)2.61320.4520.302Find the p-value. (Round your answer to four decimal places.)p-value .0349State your conclusion.F4 --0.2184-Responses/submit/dep=30597856&tags=autosave#question4806908_11%5617&7fafoX when the number of salespeople is held constant. As the number of salespeople increases by 1, sales are expected8DIIf10DDI12 insertPAprt sc[backspacehomenumlockendF11:00 PM11/29/20227homepg up004 (d) At a = 0.05, test for the significance of the coefficient of number of salespeople.State the null and alternative hypotheses. (Enter != for # as needed.)B₂=0ß₂!= 0HoHaFind the value of the test statistic. (Round your answer to two decimal places.)69Find the p-value. (Round your answer to four decimal places.)p-value = .5097XState your conclusion.O Reject Ho. There is sufficient evidence to conclude that B₂ is significant.O Do not reject Ho. There is insufficient evidence to conclude that , is significant.O Reject Ho. There is insufficient evidence to conclude that is significant.O Do not reject Ho. There is sufficient evidence to conclude that B₂ is significant.(e) If the company uses $48,000 in advertisement and has 790 salespeople, what are the expected sales? Give your answer in dollars.$37931.97XNeed Help?Submit Answer55°FHeavy sleetRead It2hp□W

Given that, Dependent variable (y) = Sales Independent variables: x1 = Advertising expenditures x2 =…

Answered: (a) Write the regression equation. ŷ=…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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In the regression equation Y = 85.65 + 0.70X1 - 3.43X2, the intercept is a. 0.70 b. -3.43 c. 1 d. 85.65
Data 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.
An individual wants to determine how much money a boy scout earns from selling popcorn (Y-variable) based on the length of time (in days) that they went out selling (X-variable). Using the following linear regression equation Ŷ = 5 + 20X: a. State the value of the intercept AND the value of the slope (2 points) b. Based on the given regression equation, what can you determine about the direction of the relationship between X and Y (i.e. is it positive or negative)? (2 points) c. If a boy scout sells popcorn for 4 days, how much money is he predicted to earn? (2 points)
DATAfile: NFLPassing The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the average number of passing yards per attempt (Yards/Attempt) and the percentage of games won (WinPct) for a random sample of 10 NFL teams for the 2011 season.t Team Yards/Attempt WinPct Arizona Cardinals 6.5 50 Atlanta Falcons 7.1 63 Carolina Panthers 7.4 38 Chicago Bears 6.4 50 Dallas Cowboys 7.4 50 New England Patriots 8.3 81 Philadelphia Eagles 7.4 50 Seattle Seahawks 6.1 44 St. Louis Rams 5.2 13 Tampa Bay Buccaneers 6.2 25
Using the given equation for the regression line shown, determine the amount of time required to completely burn the candle. [2C] A Burning Candle 35.0 30.0 25.0 y = -0.2x + 30 20.0 15.0 10.0 5.0 0.0 20 40 60 80 100 Time (min) Height of Candle (cm)
A study investigating the relationship between a country's annual gross domestic product x (in trillions of dollars) and carbon dioxide emissions y(in millions of metric tons) yielded r = 0.87, se = 141.9 , and the regression equation y-hat = 199.5x + 56.0. For each additional trillion dollars in %3D gross domestic product, carbon dioxide emissions increases by about 0.87 million metric tons, on average increases by about 199.5 million metric tons, on average changes by an amount that cannot be determined from the information given O increases by about 141.9 million metric tons, on average increases by about 56.0 million metric tons, on average
A teacher wants to form a linear regression equation to predict a student's score on the final based on the number of hours they spent studying for it. Final scores are in percents. y=2x + 60 R-Squared = 0.65 What does the y-intercept mean in terms of the situation? O If a student doesn't study for the final, their score on the final would be 60%. O If they doesn't study for the final their score would be 65%. O The student should study for the final. O A ripe Mango. O If a student doesn't study for the final, their score would be 2%.
A teacher wants to form a linear regression equation to predict a student's Score on the final based on the number of hours they spent studying for it. Final scores are in percents. y=2x + 60 R-Squared = 0.65 %3D What does the slope mean in terms of the situation? O For each additional hour a student studies, their grade on the final increases by 2%. O For each additional 2 hours a student student studies, their score on the final increases by 1%. O Every hour a student studies, increases their score on the final. O Always choose C. O The more a student studies, the better they will do on the final.
Statistics professor wants to use the number of hours (x) a student studies for a statistics final exam to predict the final exam score (y). A regression model was fit based on data collected from a class during the previous semester, with the following results: (y hat): y = 35.0 + 3X What is the slope? a. Yb. 35.0c. 3d. X
(d) Write out the regression equation. (Use 2 decimal places.) x1 = + x2 + x3 + x4 If x2 (production costs) and x4 (book sales) were held fixed but x3 (promotional costs) were increased by 0.7 million dollars, what would you expect for the corresponding change in x1 (box office receipts)? (Use 2 decimal places.)(e) Test each coefficient in the regression equation to determine if it is zero or not zero. Use level of significance 5%. (Use 2 decimal places for t and 3 decimal places for the P-value.) t P-value β2 β3 β4 (f) Find a 90% confidence interval for each coefficient. (Use 2 decimal places.) lower limit upper limit β2 β3 β4
The fitted regression is Sales = 842 − 37.5 Price. (a-1) If Price = 1, what is the prediction for Sales? (Round your answer to 1 decimal place.) (b) If Price = 20, what is the prediction for Sales?

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