The worksheet Revenue in the Chp 17 HW problems data worksheet on Moodleshows quarterly revenue over the period 2018-2023.a) Fit a seasonal regression model with trend to the data. Is the model significant atα = 0.05? What is the equation of the fit line. Interpret the model parameters inthe context of the problem.b) Use the regression model of part a) to make quarterly sales forecasts and an annualsales forecast for the next year, i.e., 2024. о1 Year2AB0DEFGHJKMNQuarterRevenuetQ1Q2Q32018 Qtr1533011003Qtr2671320104Qtr3690630015Qtr47986400062019 Qtr1510151007Qtr2617860108Qtr3637670019Qtr47457000102020 Qtr15530910011Qtr265381001012Qtr368301100113Qtr4807312000142021 Qtr161311310015Qtr270701401016Qtr3725717Qtr48803182022 Qtr1658519Qtr27697222222222222Qtr38184Qtr4100962023 Qtr17205Qtr28599Qtr38950Qtr4103835676222222150011600017100180101900200021232410000100-000-01282930<Ready47°FCloudySalesSterlingRevenue+Accessibility: Good to goQ SearchPΟQRSTUENG<W11:07 PM4/6/2024100%PRE

Given,the data worksheet on moodle shows quarterly revenue over the period…

Answered: a) Fit a seasonal regression model with…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construct and interpret a 99% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,634 thousand barrels per day. The equation of the regression line is y=- 1.190x+16,230.863. Oil produced, x 5,811 5,659 5,450 5,168 5,094 Oil imported, y 9,320 9,621 10,030 10,126 10,157 5,739 9,118 LL OA. There is a 99% chance that the predicted amount of oil imported is between per day produced. 5,049 10,066 Construct and interpret a 99% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,634 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to two decimal places as needed.) and…
A regression is run to determine if there is a relationship between the age of a company (x) and its profit (y) in thousands of dollars. The result of the regression were: y=ax+b, a=3.5, b=50, r=0.98 Use this to predict the profit of a company whichhas been in business for 20 years.
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (b) x = 10 wins (c) x = 19 wins (d) x = 15 wins E Click the icon to view the table of numbers of wins and earned run average. The equation of the regression line is y =x+ (Round to two decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Choose the correct graph below. OA. OB. OC. OD. AERA 6- AERA AERA AERA 2- 2- 2- 0- 0- 12 18 24 12 18 24 12 18 24 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below…
1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable. 2. Present the simple lincar regression equation, identify and explain the cocfficient of determination, intercept and regression coefficient, and significance of F-test. Based on this analysis, is your regression equation "good for use"? Explain. 3. Provide a numeric example of how this regression equation may be used to predict students starting salaries. 4. Develop a multiple regression equation for starting salaries using School Ranking, GPA, and Experience as independent variables. Is this regression equation "good for use? Explain. 5. If the multiple regression equation in the previous question is not "good for use", how would you suggest improving this multiple regression equation? Present the improved multiple regression equation. Give a numeric example of how this improved multiple…
STER. 1. Wine Consumption. The table below gives the U.S. adult wine consumption, in gallons per person per year, for selected years from 1980 to 2005. a) Create a scatterplot for the data. Graph the scatterplot Year Wine below. Consumption 2.6 b) Determine what type of model is appropriate for the 1980 data. 1985 2.3 c) Use the appropriate regression on your calculator to find a Graph the regression equation in the same coordinate plane below. d) According to your model, in what year was wine consumption at a minimum? A e) Use your model to predict the wine consumption in 2008. 1990 2.0 1995 2.1 2000 2.5 2005 2.8
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (b) x = 10 wins (c) x = 19 wins (d) x = 15 wins Click the icon to view the table of numbers of wins and earned run average. The equation of the regression line is y = x+. (Round to two decimal places as needed.)
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) mported by a country, for the last seven years. Construct and interpret a 95% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,508 thousand barrels per day. The equation of the regression line is y = - 1.120x + 15,839.271. Oil produced, x 5,684 5,654 5,452 5,157 5,061 5,030 5,826 9,680 10,041 10,154 10,121 10,060 Oil imported, y 9,304 9,105 Construct and interpret a 95% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,508 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) and O A. We can be 95% confident that when the amount of oil produced is 5,508 thousand barrels, the…
The following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers): A.What would be the typical linear regression equation for the number of sales? B.Make the sales forecast for period 15 of next year. C. Make the sales forecast for period 17 of next year. D. What is the standard error for the data?
The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906
Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker
Canada's trade balance with the rest of the world has been steadily increasing over the past several years. It is well known that the U.S. is Canada's leading trade partner. Is there a predictable linear relationship between our total trade balance and our trade balance with the U.S.? Develop a regression model to predict the trade balance with the U.S. by our trade balance with the rest of the world. Comment on the strength of the model. Develop a time-series trend line for trade balance with the rest of the world by using the time periods given. Forecast total trade balance with the rest of the world for 2020 using this equation. Trade Balance ($ millions) Year Rest of the World U.S. 2010 2,290 4,991 2011 2,486 4,709 2012 2,776 4,641 2013 2,648 5,220 2014 3,068 5,041 2015 3,688 4,750 2016 4,111 4,321 2017 4,172 4,699 2018 3,669 4,777 2019 3,493 4,809 question 1: y̅ = ?+?x question…

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS