In a study of variables that affect productivity in the retail grocery trade, W.S. Gooduses value added per work-hour to measure the productivity of retail grocery outlets.¹He defines "value added" as "the surplus [money generated by the business] availableto pay for labor, furniture and fixtures, and equipment." Data consistent with the re-lationship between value added per work-hour y and the size x of a grocery outlet de-scribed in Good's article are shown in Table 13.2 for 10 fictitious grocery outlets.Choose a model to relate y to x.Data on Store Size and Value AddedStoreValue Added per Work-Hour, y (S)4.083.403.513.092.921.944.113.16123789456103.753.60Size of Store (thousand square feet), x21.012.025.210.430.96.819.614.525.019.1

Regression equation is used to predict the future value. It explains the relationship between the…

Answered: In a study of variables that affect…

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

An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month (2018) Volume of Production (Units) Total Costs ($) Jan 500 6000 Feb 350 4000 Mar 450 5000 Apr 550 5400 May 600 5900 Jun 400 4000 Jul 400 4200 Aug 350 3900 Sept 400 4300 Oct 600 6000 Nov 700 6400 Dec 750 7000 1) Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? 2) Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in…
I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset are: Quantity sold in the city for that month: Measured in thousands of units Price: measured in dollars Average Income in the city: Measured in thousands of dollars Ads: Average number of ads run in stores for that city during that month. Price of a substitute product: measured in dollars Population of the city: measured in thousands of people The dataset is on Canvas and, using Excel or any other statistical software, please answer the following questions: 1. Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. 2. Take the logs of the variables, and estimate the demand function. a. Interpret the R-square. b. Interpret the coefficients for logP and logPsub c. Interpret the p-values associated with each independent…
Researchers are interested in whether or not shoe size could predict height. Data was collected from 25 students. Students reported their height and shoe size. (Source: Intro to Statistics by Gould & Ryan). Height = 51.46 + 1.728 (Shoe Size) 74 72 70 68 66 64 62 60 4 7 9. 10 11 12 13 Shoe Size a. According to the graph, define the input, including units. b. According to the graph, define the output variables, including units. b. Use the equation of the regression line to interpret the rate of change, including units. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIU S Paragraph Arial 10pt A v Ix *G白CQ ... x? X2 ABC 甲图 Ť (i} > II !!! +] > 四用 S田 Height (in inches)
An economist was interested in the relation between the disposable income of a family and the amount of money used for food per month. He did a preliminary study on eight randomly selected lower income families. (Each family was of the same size; father, mother and two children). The economist’s data are given in the table below. Food cost (Y) (in hundreds of rand) 55 60 42 40 37 26 39 43 Family disposable income(X) (in hundreds of rand) 30 36 27 20 16 24 19 25 Find the regression linear equation. What is the predicted food cost if the family disposable income is R1800? Find the correlation coefficient & Interpret r. Find the Coefficient of Determination & Interpret the R2.
The following table gives the quantity demanded of ice cream (Qic) in kgs per year in Sardinia (Italy), its price (Pic) in $ per kg, consumers’ income (I) in $, the temperature (T) in Celsius, and the price of cappuccino (Pc) in $ per kg: Year Qic Pic ($/kg) I ($) T Pc ($/kg) 2000 72000 11 2000 20 14 2001 81000 10 2100 24 15 2002 90000 9 2200 25 15 2003 99000 7 2305 26 16 2004 108000 6 2407 30 17 2005 126000 4 2500 32 18 2006 117000 7 2610 26 16 2007 117000 8 2698 25 16 2008 135000 5 2801 31 18 2009 135000 5 2921 31 18 2010 144000 4 3000 34 20 2011 180000 2 3099 36 21 2012 162000 5 3201 33 19 2013 171000 4 3308 35 21 2014 153000 6 3397 30 18 2015 180000 3 3501 35 22 2016 171000 4 3689 33 20 2017 180000 3 3800 36 23…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes O and total cost data for a manufacturing operation. O Production Volume (units) Total Cost ($) 400 4100 450 4600 500 5600 600 6400 700 7400 750 8400 N The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation ŷ = -524.58+11.66z. a. The company's production schedule shows that 550 units must be produced next month. Predict the total cost for next month. ŷ* = (to 2 decimals) b. Develop a 98% prediction interval for the total cost for next month. X (to 2 decimals) 8 t-value (to 3 decimals) 8pred (to 2 decimals) Prediction Interval for…
The following data measured the stress hormone of steelhead fish as a function of the oxygen content in the water. These data are given below: oxygen 25 36 48 59 62 72 80 100 100 137 hormone 155 184 180 220 280 163 230 222 241 350 Construct a scatterplot and discuss its characteristics Does there appear to be a relationship between water oxygen levels and hormone levels?
An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month Production Volume (units) Total Costs ($) January 2018 February 2018 500 6,000 350 4,000 March 2018 450 5,000 April 2018 550 5,400 May 2018 600 5,900 June 2018 400 4,000 July 2018 August 2018 September 2018 400 4,200 350 3,900 400 4,300 October 2018 600 6,000 November 2018 700 6,400 December 2018 750 7,000 Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? * I. The monthly total costs will increase by $7.6437 for every one-unit increase in the…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,700 450 5,700 550 6,100 600 6,600 700 7,100 750 7,700 A) Compute b1 and b0 (to 1 decimal)b1 b0 Complete the estimated regression equation (to 1 decimal). = + x B) What is the variable cost per unit produced (to 1 decimal)?$ C) Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1.r2 = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? % D) The company's production schedule shows 500 units must be produced next…
The following table gives estimates of the percent of a certain country's population below the poverty level for 1998–2008. Year Percent 1998 12.8 2000 11.2 2002 12.1 2004 12.7 2006 12.9 2008 13.2 Find the least squares line that relates years to percent below the poverty level. (Let x = 0 represent the year 1998. Enter a mathematical expression.
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 3,700 450 4,700 550 5,100 600 5,600 700 6,100 750 6,700 Compute b1 and b0 (to 1 decimal).b1 b0 Complete the estimated regression equation (to 1 decimal). = + x What is the variable cost per unit produced (to 1 decimal)?$ Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1.r2 = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? % The company's production schedule shows 500 units must be produced next month. What…
he table shows the minimum wage rates for the United States during different years. Year 1978 1979 1980 1990 1991 1996 1997 2007 2008 2009 Minimum hourly wage ($) 2.65 2.90 3.35 3.80 4.25 4.75 5.15 5.85 6.55 7.25 Write the least squares regression equation that models the data. Let x = time in years since 1900 and let y = minimum hourly wage. Use the equation to estimate the minimum hourly wage of a U.S. worker in 2025. Show your work. Answer:

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