Statistics for Business and Economics (13th Edition)
13th Edition
ISBN: 9780134506593
Author: James T. McClave, P. George Benson, Terry Sincich
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Videos
Textbook Question
Chapter 14.8, Problem 14.39LM
Retail sales in Quarters 1–4 over a 10-year period for a department store are shown (in hundreds of thousands of dollars) in the table below.
a. Write a regression model that contains trend and seasonal components to describe the sales data.
b. Use least squares regression to fit the model. Evaluate the fit of the model.
c. Use the regression model to forecast the quarterly sales during year 11. Give 95% prediction intervals for the forecasts.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
-Using the data in Table 6–11, answer the following:
What is the slope?
What is the intercept?
Write the regression equation.
Calculate a regression forecast for month 25.
Q. Table provided gives data on gross domestic product (GDP) for the United States for the years 1959–2005.
a. Plot the GDP data in current and constant (i.e., 2000) dollars against time.
b. Letting Y denote GDP and X time (measured chronologically starting with 1 for 1959, 2 for 1960, through 47 for 2005), see if the following model fits the GDP data:
Yt = β1 + β2 Xt + ut
Estimate this model for both current and constant-dollar GDP.
c. How would you interpret β2?
d. If there is a difference between β2 estimated for current-dollar GDP and that estimated for constant-dollar GDP, what explains the difference?
e. From your results what can you say about the nature of inflation in the United States over the sample period?
Using the data in Table 6–11, answer the following:a. What is the slope?b. What is the intercept?c. Write the regression equation.d. Calculate a regression forecast for month 25.
Chapter 14 Solutions
Statistics for Business and Economics (13th Edition)
Ch. 14.1 - Explain in words how to construct a simple index.Ch. 14.1 - Explain in words how to calculate the following...Ch. 14.1 - Explain in words the difference between Laspeyres...Ch. 14.1 - The table below gives the prices for three...Ch. 14.1 - Refer to Exercise 14.4. The next table gives the...Ch. 14.1 - Annual median family income. The table below lists...Ch. 14.1 - Annual U.S. craft beer production. While overall...Ch. 14.1 - Quarterly single-family housing starts. The...Ch. 14.1 - Spot price of natural gas. The table shown in the...Ch. 14.1 - Employment in farm and nonfarm categories....
Ch. 14.1 - GOP personal consumption expenditures. The gross...Ch. 14.1 - GDP personal consumption expenditures (contd)....Ch. 14.1 - Weekly earnings for workers. The table in the next...Ch. 14.1 - Production and price of metals. The level or price...Ch. 14.2 - Describe the effect of selecting an exponential...Ch. 14.2 - A monthly time series is shown in the table to the...Ch. 14.2 - Annual U.S. craft beer production. Refer to the...Ch. 14.2 - Foreign fish production. Overfishing and pollution...Ch. 14.2 - Yearly price of gold. The price of gold is used by...Ch. 14.2 - Personal consumption in transportation. There has...Ch. 14.2 - OPEC crude oil imports. The data in the table...Ch. 14.2 - SP 500 Stock Index. Standard Poors 500 Composite...Ch. 14.5 - How does the choice of the smoothing constant w...Ch. 14.5 - Refer to Exercise 14.4 (p. 14-9). The table with...Ch. 14.5 - Annual U.S. craft beer production. Refer to...Ch. 14.5 - Quarterly single-family housing starts. Refer to...Ch. 14.5 - Consumer Price Index. The CPI measures the...Ch. 14.5 - OPEC crude oil imports. Refer to the annual OPEC...Ch. 14.5 - SP 500 Stock Index. Refer to the quarterly...Ch. 14.5 - SP 500 Stock Index (contd). Refer to Exercise...Ch. 14.5 - Monthly gold prices. The fluctuation of gold...Ch. 14.6 - Annual U.S. craft beer production. Refer to the...Ch. 14.6 - Annual U.S. craft beer production (contd). Refer...Ch. 14.6 - SP 500 Stock Index. Refer to your exponential...Ch. 14.6 - SP 500 Stock Index (contd). Refer to your Holt...Ch. 14.6 - Monthly gold prices. Refer to the monthly gold...Ch. 14.6 - US school enrollments. The next table reports...Ch. 14.8 - The annual price of a finished product (in cents...Ch. 14.8 - Retail sales in Quarters 14 over a 10-year period...Ch. 14.8 - What advantage do regression forecasts have over...Ch. 14.8 - Mortgage interest rates. The level at which...Ch. 14.8 - Price of natural gas. Refer to Exercise 14.9 (p....Ch. 14.8 - A gasoline tax on carbon emissions. In an effort...Ch. 14.8 - Predicting presidential elections. Researchers at...Ch. 14.8 - Life insurance policies in force. The table below...Ch. 14.8 - Graphing calculator sales. The next table presents...Ch. 14.8 - Prob. 14.47ACICh. 14.9 - Define autocorrelation. Explain why it is...Ch. 14.9 - For each case, indicate the decision regarding the...Ch. 14.9 - What do the following Durbin-Watson statistics...Ch. 14.9 - Company donations to charity. Refer to the Journal...Ch. 14.9 - Forecasting monthly car and truck sales. Forecasts...Ch. 14.9 - Predicting presidential elections. Refer to the...Ch. 14.9 - Mortgage interest rates. Refer to the data on...Ch. 14.9 - Price of natural gas. Refer to the annual data on...Ch. 14.9 - Life insurance policies in force. Refer to the...Ch. 14.9 - Modeling the deposit share of a retail bank....Ch. 14 - Insured Social Security workers. Workers insured...Ch. 14 - Insured Social Security workers (contd). Refer to...Ch. 14 - Retail prices of food items. In 1990, the average...Ch. 14 - Demand for emergency room services. With the...Ch. 14 - Mortgage interest rates. Refer to the annual...Ch. 14 - Price of Abbott Labs stock. The yearly closing...Ch. 14 - Price o f Abbott Labs stock (contd). Refer to...Ch. 14 - Prob. 14.65ACICh. 14 - Prob. 14.66ACICh. 14 - Quarterly GOP values (contd). Refer to Exercise...Ch. 14 - Prob. 14.68ACICh. 14 - Prob. 14.69ACICh. 14 - Prob. 14.70ACICh. 14 - IBM stock prices. Refer to Example 14.1 (p. 14-5)...Ch. 14 - Prob. 14.72ACI
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Corvette, Ferrari, and Jaguar produced a variety of classic cars that continue to increase in value. The data showing the rarity rating (1–20) and the high price ($1000s) for 15 classic cars is contained in the Excel Online file below. Construct a spreadsheet to answer the following questions.arrow_forwardRegression and Predictions. Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. Tips Using the bill/tip data, find the best predicted tip amount for a dinner bill of $100. What tipping rule does the regression equation suggest?arrow_forwardQ1. The table provided gives data on indexes of output per hour (X) and real compensation per hour (Y) for the business and nonfarm business sectors of the U.S. economy for 1960–2005. The base year of the indexes is 1992 = 100 and the indexes are seasonally adjusted. a. Plot Y against X for the two sectors separately. b. What is the economic theory behind the relationship between the two variables? Does the scattergram support the theory? c. Estimate the OLS regression of Y on X. Note: on the table ( 1. Output refers to real gross domestic product in the sector. 2. Wages and salaries of employees plus employers’ contributions for social insurance and private benefit plans. 3. Hourly compensation divided by the consumer price index for all urban consumers for recent quarters.) Thank you!arrow_forward
- Using the data in Table 6–11, calculate a 3-month moving average forecast for month 12.arrow_forwardStatistics Canada produces consumer price indexes for several different categories. Shown here are the percentage changes in consumer price indexes over a period of 22 years for durable goods, semidurable goods, and nondurable goods. Also displayed are the percentage changes in total goods price index. Use these data and multiple regression to develop a model that attempts to predict the total goods index by the other three variables. Comment on the result of this analysis. Year TotalGoods DurableGoods SemidurableGoods NondurableGoods 1 85.7 89.4 91.9 83.2 2 86.4 90.4 92.5 83.8 3 87.8 92.5 93.4 85.2 4 86.8 96.0 94.2 81.6 5 88.4 99.0 94.9 82.9 6 89.9 100.8 95.4 84.4 7 91.2 101.6 97.0 86.0 8 91.4 101.5 97.7 86.1 9 93.1 101.5 99.2 88.4 10 96.0 100.8 99.6 93.3 11 98.4 100.1 100.3 97.4 12 100 100 100 100 13 101.9 99.2…arrow_forwardWrite a detail note on REGRESSION?arrow_forward
- Part I. Run two regressions in Excel using the provided Excel file “Layoffs”.The Excel file Layoffs provides data on 50 manufacturing workers who lost their jobs due to layoffs. The data includes the following list of variables:Weeks – the number of weeks a manufacturing worker has been without a jobAge – the age of the workerEducation – the number of years of education of the workerMarried – a dummy variable, equal to 1 if the worker is married, 0 otherwiseHead – a dummy variable, equal to 1 if the worker is a head of household, 0 otherwiseTenure – the number of years on the previous jobManager – a dummy variable, equal to 1 if the worker had a management occupation, 0 otherwise Sales – a dummy variable, equal to 1 if the worker had an occupation in sales, 0 otherwise 1. Run a simple regression with a dependent variable Weeks and an independent variable Age. Create the regular and standardized residual plots for the simple regression. 2. Run a multiple regression with a dependent…arrow_forwardThe file P02_26.xlsx lists sales (in millions of dollars) of Dell Computer during the period 1987–1997 (where year 1 corresponds to 1987). Year Sales 1 69 2 159 3 258 4 389 5 546 6 890 7 2014 8 2873 9 3475 10 5296 11 7759 a. Fit a power and an exponential trend curve to these data. Which fits the data better? b. Use your part a answer to predict 1999 sales for Dell. c. Use your part a answer to describe how the sales of Dell have grown from year to year.arrow_forwardam. 13.arrow_forward
- Applying the Concepts and SkillsIn Exercises, we repeat the information from Exercises. For each exercise here, discuss what satisfying Assumptions 1–3 for regression inferences by the variables under consideration would mean.ExercisesApplying the Concepts and SkillsIn each of Exercises,a. find the regression equation for the data points.b. graph the regression equation and the data points.c. describe the apparent relationship between the two variables under consideration.d. interpret the slope of the regression line.e. identify the predictor and response variables.f. identify outliers and potential influential observations.g. predict the values of the response variable for the specified values of the predictor variable, and interpret your results.Tax Efficiency.Tax efficiency is a measure, ranging from 0 to 100, of how much tax due to capital gains stock or mutual funds investors pay on their investments each year; the higher the tax efficiency, the lower is the tax. In the article…arrow_forwardThe November 24, 2001, issue of The Economist published economic data for 15 industrialized nations. Included were the percent changes in gross domestic product (GDP), industrial production (IP), consumer prices (CP), and producer prices (PP) from Fall 2000 to Fall 2001, and the unemployment rate in Fall 2001 (UNEMP). An economist wants to construct a model to predict GDP from the other variables. A fit of the model GDP = , + P,IP + 0,UNEMP + f,CP + P,PP + € yields the following output: The regression equation is GDP = 1.19 + 0.17 IP + 0.18 UNEMP + 0.18 CP – 0.18 PP Predictor Coef SE Coef тР Constant 1.18957 0.42180 2.82 0.018 IP 0.17326 0.041962 4.13 0.002 UNEMP 0.17918 0.045895 3.90 0.003 CP 0.17591 0.11365 1.55 0.153 PP -0.18393 0.068808 -2.67 0.023 Predict the percent change in GDP for a country with IP = 0.5, UNEMP = 5.7, CP = 3.0, and PP = 4.1. a. b. If two countries differ in unemployment rate by 1%, by how much would you predict their percent changes in GDP to differ, other…arrow_forwardUse the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSON
The Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. Freeman
Introduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
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
Time Series Analysis Theory & Uni-variate Forecasting Techniques; Author: Analytics University;https://www.youtube.com/watch?v=_X5q9FYLGxM;License: Standard YouTube License, CC-BY
Operations management 101: Time-series, forecasting introduction; Author: Brandoz Foltz;https://www.youtube.com/watch?v=EaqZP36ool8;License: Standard YouTube License, CC-BY