BASIC BUSINESS STATISTICS-STUD.SOLN.MAN
14th Edition
ISBN: 9780134685045
Author: BERENSON
Publisher: PEARSON
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Chapter 15, Problem 20PS
Refer to Problem 14.8 on page 542. Perform a multiple
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Please help me better understand proble and how to calculate predicted vale of Allen's final exam.
In a accounting course, a linear regression equation was computed to predict the final exam score from the score on the midterm exam. The equation of the least-squares regression line was Y= 10 + 0.85X. Y represents the final exam score, and X is the midterm exam score.
QUESTION: Suppose Allen scores 83 on the midterm exam. What would be the predicted value of his score on the final exam (assuming no extrapolation error)?
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You want to estimate a model on car production (units) based on the previous year data on the number of cars sold (units), price of cars ($/unit), and total sales of cars ($). The regression
would be car production on the number of cars sold, price of cars, total sales of cars, and a constant. Describe the problem with this model.
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Please help me understand this problem more in depth. A researcher is investigating possible explanations for deaths in traffic accidents. He examined data from 2000 for each of the 52 cities randomly selected in the US. The data included information on the following variables: Deaths: The number of deaths in traffic accidents per city Income: The median income per city As part of his study, he ran the following simple linear regression model attached in photo.
Question: Based on the above results, the researcher tested the hypotheses: Ho: B1=0 versus B1 not equal to 0, versus using T test. What do we know about the test statistic of the test? Based on the approximate p-value, what's the conclusion?
Chapter 15 Solutions
BASIC BUSINESS STATISTICS-STUD.SOLN.MAN
Ch. 15 - The following is the quadratic regression equation...Ch. 15 - Business actively recruit business student with...Ch. 15 - A study was conducted on automobile engines to...Ch. 15 - Prob. 4PSCh. 15 - In the production of printed circuit boards,...Ch. 15 - An automotive sales manager wishes to examine the...Ch. 15 - Researchers wanted to investigate the relationship...Ch. 15 - Prob. 8PSCh. 15 - Prob. 9PSCh. 15 - Prob. 10PS
Ch. 15 - Using the data of Problem 15.4 on page 600, stored...Ch. 15 - Using the data of Problem 15.6 on page 601, stored...Ch. 15 - Using the data of Problem 15.6 on page 601 stored...Ch. 15 - If the coefficient of determination between two...Ch. 15 - If the coefficient of determination between two...Ch. 15 - Prob. 16PSCh. 15 - Refer to Problem 14.5 on page 542. Perform a...Ch. 15 - Refer to Problem 14.6 on page 542. Perform a...Ch. 15 - Refer to Problem 14.7 on page 542. Perform a...Ch. 15 - Refer to Problem 14.8 on page 542. Perform a...Ch. 15 - Prob. 21PSCh. 15 - Prob. 22PSCh. 15 - Prob. 23PSCh. 15 - You need to develop a model to predict the asking...Ch. 15 - Accounting Today identified top public accounting...Ch. 15 - How can you evaluate whether collinearity exists...Ch. 15 - Prob. 27PSCh. 15 - Prob. 28PSCh. 15 - A Specialist in baseball analytics has expanded...Ch. 15 - In the production of printed circuit boards,...Ch. 15 - Hemlock Farms is a community located in the Pocono...Ch. 15 - Prob. 32PSCh. 15 - Prob. 33PSCh. 15 - Prob. 34PSCh. 15 - You are a real estate broker who wants to compare...Ch. 15 - You are a real estate broker who wants to compare...Ch. 15 - Financial analysts engage in business valuation to...Ch. 15 - Prob. 38PSCh. 15 - A molding machine that contains different cavities...Ch. 15 - The file Cites contains a sample of 25 cities in...Ch. 15 - In problem 15.32-15.36 you developed multiple...
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- Olympic 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_forwardTable 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_forwardThe following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forward
- 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.arrow_forwardThe data set was obtained from 21 days of operation of a plant for the oxidation of ammonia to nitric acid. It is desired to fit a multiple linear regression model to predict Y = stack loss which is 10 times the percentage of the ingoing ammonia to the plant that escapes from the absorption column unabsorbed, as Y = Bo + B1Xair.flow + B2 water.temp + B3 xacid.conc Air.Flow represents the rate of operation of the plant. Water.Temp is the temperature of cooling water circulated through coils in the absorption tower. Acid.Conc is the concentration of the acid circulating, minus 50, times 10. This is the result of the best subsets regression. |Summary of best subsets, variable(s): stack.loss (stt 151astackloss) Adjusted R square and standardized regression coefficients for each submodel Adjusted R square 0.898623 No. of Effects Air. Flow Water.Temp Acid.Conc. Subset No. 1 2 0.604950 0.402523 This is the result of the forward stepwise regression. Degr. of Freedom P to enter 0.000000 Effect…arrow_forwardPlease use linear regression test statistics, and defined everything -- all parts.arrow_forward
- 13) Use computer software to find the multiple regression equation. Can the equation be used for prediction? An anti-smoking group used data in the table to relate the carbon monoxide( CO) of various brands of cigarettes to their tar and nicotine (NIC) content. 13). CO TAR NIC 15 1.2 16 15 1.2 16 17 1.0 16 6. 0.8 1 0.1 1 8. 0.8 8. 10 0.8 10 17 1.0 16 15 1.2 15 11 0.7 9. 18 1.4 18 16 1.0 15 10 0.8 9. 0.5 18 1.1 16 A) CO = 1.37 + 5.50TAR – 1.38NIC; Yes, because the P-value is high. B) CÓ = 1.37 - 5.53TAR + 1.33NIC; Yes, because the R2 is high. C) CO = 1.25 + 1.55TAR – 5.79NIC; Yes, because the P-value is too low. D) CO = 1.3 + 5.5TAR - 1.3NIC; Yes, because the adjusted R2 is high. %3Darrow_forwardDefine both x and y in all problems. x is the cause, and y is the effect. This is the most important step when doing linear regression, otherwise, all the remanding parts will be wrong.arrow_forwardplease show calc functions ti-84arrow_forward
- I need help with determining the p-value in attached question. Please make sure to round to three decimal places for the p-value as needed.arrow_forwardAn engineer performed an experiment to determine the effect of CO2 pres- sure, CO, temperature, peanut moisture, CO2 flow rate, and peanut particle size on the total yield of oil per batch of peanuts. Table B.7 summarizes the experimental results. e. Find a 95% CI for the regression coefficient for temperature for both models in part d. Discuss any differences.arrow_forwardDefine both x and y in all problems. x is the cause, and y is the effect. This is the most important step when doing linear regression, otherwise, all the remanding parts will be wrong.arrow_forward
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