Concept explainers
Using the data of Problem 15.6 on page 601, stored in HondaPrices, Perform a natural logarithm transformation of the dependent variables (prices). Using the transformed dependent variable and the age as the independent variables, perform a
a. State the regression equation.
b. Predict the mean price for a five-year-old Honda Civic LX.
c. Perform a residual analysis of the results and determine whether the regression assumptions are valid.
d. At The 0.05 level of significance, is there a significant relationship between the natural logarithm of price and age?
e. Interpret the meaning of the coefficient of determination.
f. Compare the adjusted
g. Compare your results with those in Problem 15.6. Which model is better? Why?
Want to see the full answer?
Check out a sample textbook solutionChapter 15 Solutions
EBK BASIC BUSINESS STATISTICS
- Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forwardTable 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?arrow_forward
- Life 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_forwardTable 3 gives the annual sales (in millions of dollars) of a product from 1998 to 20006. What was the average rate of change of annual sales (a) between 2001 and 2002, and (b) between 2001 and 2004?arrow_forwardThe U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. What proportion of variation in the number of complaints can be explained by hourly wages? From the results shown above, write the regression equation If wages were increased by $1.00, what is the expected effect on the number of complaints received per employee?arrow_forward
- The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000arrow_forwarda. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 1 decimal).arrow_forwardA Realtor examines the factors that influence the price of a house in Arlington, Massachusetts. He collects data on recent house sales (Price) and notes each house’s square footage (Sqft) as well as its number of bedrooms (Beds) and number of bathrooms (Baths). Which of the following assumptions is NOT made when estimating regression models? a. There is a linear relationship between the explanatory and response variables b. All of the relevant explanatory variables have been included in the model c. All of the explanatory variables are independent d. All of the explanatory variables are positively correlated with the response variable.arrow_forward
- The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?arrow_forwardThe following data give the yearly inflation rate and money supply growthrate (both measured in percentage) for 51 countries. A simple regression of Infla-tion on Growth yields the following information from RegressIt output: (a) What is the linear relationship implied by these data? (b) For a country with an 6% money supply growth, what would be theexpected inflation? (This means Growth= 6 as it is measured in percentage.) (c) A simplistic monetarist claims that a 1% increase in the money supplygrowth rate would result in a corresponding 1% increase in inflation. In otherwords, for the relationship of Inflation = β0 + β1Growth, the null hypothesis isβ1 = 1. Do the regression results support this null hypothesis?arrow_forwardThe electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2). The past year’s historical data are available and are presented in the following table: Fit a multiple linear regression model to these data.arrow_forward
- Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage LearningAlgebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillAlgebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:CengageCollege AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning