Statistical Techniques in Business and Economics
16th Edition
ISBN: 9780077639723
Author: Lind
Publisher: Mcgraw-Hill Course Content Delivery
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 13, Problem 4SR
To determine
Test whether the
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
The St. Lucian Government is interested in predicting the number of weekly riders on the public buses using the following variables:
• • • •
Price of bus trips per weekThe population in the cityThe monthly income of ridersAverage rate to park your personal vehicle
Determine the multiple regression equation for the data.
What is the predicted value of the number of weekly riders if: price of bus trips per week = $24; population = $2,000,000; the monthly income of riders = $13,500; and average rate to park your personal vehicle = $150.
Interpret the coefficient of determination.
For a two-variable linear regression, if the sample correlation between the depen-
dent and independent variables is –0.7, then the independent variable explains
49% of the variation in the dependent variable. Is this statement true? Explain
your answer.
An independent researcher wants to study the factors which affected the prices set by a leading AC manufacturing company, Chester, across the country for the year 2017. She studies whether the
effect on price, of the quantity demanded of ACs by the consumers, is significant or not. She selects a random sample of 200 retail outlets of the company and estimates the following
regression equation:
P-800.75-12.58/n(Q),
(8.98) (7.64)
where is the predicted value of price of the ACs and In(Q) is the logarithm of the quantity demanded of ACs by the consumers. Standard errors are given in parentheses.
The 95% confidence interval for the slope coefficient, will be
(Round your answer to two decimal places. Enter a minus sign if your answer is negative.)
Based on the calculated confidence interval, we can say that at the 5% significance level, we will
the hypothesis that/, =0.
fail to reject
reject
Chapter 13 Solutions
Statistical Techniques in Business and Economics
Ch. 13 - Prob. 1SRCh. 13 - Prob. 1ECh. 13 - Prob. 2ECh. 13 - Bi-lo Appliance Super-Store has outlets in several...Ch. 13 - Prob. 4ECh. 13 - Prob. 5ECh. 13 - The owner of Maumee Ford-Volvo wants to study the...Ch. 13 - Prob. 2SRCh. 13 - Prob. 7ECh. 13 - Prob. 8E
Ch. 13 - Prob. 9ECh. 13 - Prob. 10ECh. 13 - Prob. 11ECh. 13 - Prob. 12ECh. 13 - Prob. 3SRCh. 13 - Prob. 13ECh. 13 - Prob. 14ECh. 13 - Prob. 15ECh. 13 - Prob. 16ECh. 13 - Prob. 17ECh. 13 - Prob. 18ECh. 13 - Prob. 19ECh. 13 - Prob. 20ECh. 13 - Prob. 4SRCh. 13 - Prob. 21ECh. 13 - Prob. 22ECh. 13 - Prob. 23ECh. 13 - Prob. 24ECh. 13 - Prob. 5SRCh. 13 - Prob. 25ECh. 13 - Prob. 26ECh. 13 - Prob. 27ECh. 13 - Prob. 28ECh. 13 - Prob. 29ECh. 13 - Prob. 30ECh. 13 - Prob. 6SRCh. 13 - Prob. 31ECh. 13 - Prob. 32ECh. 13 - Prob. 33ECh. 13 - Refer to Exercise 16. a. Determine the .95...Ch. 13 - Prob. 35ECh. 13 - A regional commuter airline selected a random...Ch. 13 - Prob. 38CECh. 13 - Prob. 39CECh. 13 - Prob. 40CECh. 13 - The table below shows the number of cars (in...Ch. 13 - Prob. 42CECh. 13 - Prob. 43CECh. 13 - Prob. 44CECh. 13 - The manufacturer of Cardio Glide exercise...Ch. 13 - Prob. 46CECh. 13 - Prob. 47CECh. 13 - Prob. 48CECh. 13 - Prob. 49CECh. 13 - Mr. William Profit is studying companies going...Ch. 13 - Prob. 51CECh. 13 - Prob. 52CECh. 13 - Prob. 53CECh. 13 - Prob. 54CECh. 13 - A regression analysis relating the current market...Ch. 13 - Prob. 56CECh. 13 - Prob. 57CECh. 13 - A consumer buying cooperative tested the effective...Ch. 13 - Prob. 59CECh. 13 - Prob. 60CECh. 13 - TravelAir.com samples domestic airline flights to...Ch. 13 - Prob. 62DECh. 13 - Refer to the Baseball 2012 data, which reports...Ch. 13 - Prob. 64DE
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
- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forward
- For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forward
- Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: What is the regression equation for all the predictors? Write a results section based on your analysis that answers the research question.arrow_forwardA study is conducted to determine if there is a relationship between the two variables, blood haemoglobin (Hb) levels and packed cell volumes (PCV) in the female population. A simple linear regression analysis was performed using SPSS. Based on the SPSS output of the ANOVA table, which of the following statements is the CORRECT interpretation? 1. The regression model statistically significantly predicts the blood haemoglobin level. 2. About 39.98 % of variance in Hb is explained by PCV. 3. The regression model does not fit the data. 4. There is significant contribution of Hb towards PCV.arrow_forwardThe Core grade point is the eventual dependent variable in a regression analysis. Look at the correlations between all variables. Is multicollinearity likely to be a problem? Why or why not?arrow_forward
- We recorded the pre-statistics course grade (in percent) and introductory statistics course grade (in percent) for 60 community college students. In this data set, no one earned a 90% for the pre-statistics course grade. How could you estimate a student’s introductory statistics course grade if she earned 90% for the pre-statistics course grade? A. Substitute 90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(90) . B. Substitute the decimal 0.90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(0.90).arrow_forwardRestaurant Digest, a famous restaurant magazine writes that the amount of tips servers get in Florida is affected by several factors including the amount of bill, number of adult diners as well as kids and the income of the diners. Use the data below to answer the following questions: Find the multiple regression model. At a level of significance of 0.03, is there a significance relationship between the amount of tip and at least one of the independent variables? What is the likely amount of tip if a group of diners spend $40.33 and had an annual income of $81,000. The diners included 4 adults and 3 kids? What percent of the variation in amount of tip is accounted for by amount of bill, annual income, number of adults and kids? Customer Amount of Tip Amount of Bill Number of adult Diners Number of kids Annual Income 1 $ 7.00 $ 48.97 5 3 100000 2 $ 4.50 $ 28.23 4 3 80000 3…arrow_forwardA linear relationship between EmployeeSalary (Dependent) and degree(independent) has the following equation : Salary = 400+0.2 (Degree). SST= 736, SSR= 385. Calculate and interpret the coefficient of determination (r2) : Select one: O a. 0.48 , 47.69 percent of the variability in employee salary can be explained by the simple linear regression equation Ob. 0.52,52.31 percent of the variability in employee salary can be explained by the simple linear regression equation Oc. 0.48, 47.69 percent of the variability in the degree earned can be explained by the simple linear regression equation F Od. 0.52, 52.31 percent of the variability in the degree earned can be explained by the simple linear regression equation Next page JUN 2 12 étv W Ps Lrarrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Algebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY