Statistics for Business and Economics (13th Edition)
13th Edition
ISBN: 9780134506593
Author: James T. McClave, P. George Benson, Terry Sincich
Publisher: PEARSON
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Chapter 11, Problem 11.120CTC
To determine
Whether the photo spall rates contribute information for the prediction of drop spall rates or not.
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2. A firm’s production function is given by:Q = 10KLThe unit capital and labour costs are 2 and 1 pounds respectively. The firm is contracted to produce2000 units.(a) Write out the optimisation problem of the firm. (b) Express this problem using a Lagrangian function. (c) Find values of K and L which fulfil the contract with minimal cost to the firm. (d) Calculate the total cost to the firm.
3. Consider the following estimated regression equation, estimated using a sample of firms, where RDis total firm spending on research and development in USD ($), Revenue is total firm revenuein USD ($), and W ages is the firms’ total spending on wages in USD ($) (standard errors inparentheses):RDd = 1000(600)+ 0.5(0.1)Revenue + 1.5(0.5)W ages,(a) Interpret the coefficients on each of the explanatory variables. (b) Which of the three coefficients are statistically significant at the 5% level of significance? Howdo you know? A researcher runs a two-sided statistical test of the null hypothesis that both the coefficients onthe explanatory variables above are jointly equal to 0.25 (mathematically, that β1 = β2 = 0.25),and reports a p-value of 0.045.(c) What does this p-value mean for the outcome of the test? (d) What would an appropriate two-sided alternative hypothesis look like?
Chapter 11 Solutions
Statistics for Business and Economics (13th Edition)
Ch. 11.1 - In each case, graph the line that passes through...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - The equation for a straight line (deterministic...Ch. 11.1 - Refer to Exercise 11.3. Find the equations of the...Ch. 11.1 - Plot the following lines: a. y 4 + x b. y = 5 2x...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - Prob. 11.7LMCh. 11.1 - Prob. 11.8LMCh. 11.1 - If a straight-line probabilistic relationship...Ch. 11.1 - Congress voting on women's issues. The American...
Ch. 11.1 - Best-paid CEOs. Refer to Glassdoor Economic...Ch. 11.1 - Estimating repair and replacement costs of water...Ch. 11.1 - Forecasting movie revenues with Twitter. A study...Ch. 11.2 - The following table is similar to Table 11.2.It is...Ch. 11.2 - Refer to Exercise 11.14. After the least squares...Ch. 11.2 - Construct a scatterplot for the data in the...Ch. 11.2 - Consider the following pairs of measurements: a....Ch. 11.2 - Use the applet Regression by Eye to explore the...Ch. 11.2 - In business, do nice guys finish first or last?...Ch. 11.2 - State Math SAT scores. Refer to the data on...Ch. 11.2 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.2 - Repair and replacement costs of water pipes. Refer...Ch. 11.2 - Joint Strike Fighter program. The Joint Strike...Ch. 11.2 - Software millionaires and birthdays. In Outliers:...Ch. 11.2 - Prob. 11.24ACICh. 11.2 - Ranking driving performance of professional...Ch. 11.2 - Sweetness of orange juice. The quality of the...Ch. 11.2 - Forecasting movie revenues with Twitter. Marketers...Ch. 11.2 - Charisma of top-level leaders. According to a...Ch. 11.2 - Ran kings of research universities. Refer to the...Ch. 11.2 - Prob. 11.30ACACh. 11.3 - Visually compare the scatterplots shown below. If...Ch. 11.3 - Calculate SSE and s2 for each of the following...Ch. 11.3 - Suppose you fit a least squares line to 26 data...Ch. 11.3 - Refer to Exercise 11.14 (p. 629). Calculate SSE,...Ch. 11.3 - Do nice guys really finish last in business? Refer...Ch. 11.3 - State Math SAT scores. Refer to the simple linear...Ch. 11.3 - Prob. 11.37ACBCh. 11.3 - Prob. 11.38ACBCh. 11.3 - Prob. 11.39ACBCh. 11.3 - Prob. 11.40ACICh. 11.3 - Prob. 11.41ACICh. 11.3 - Sweetness of orange juice. Refer to the study of...Ch. 11.3 - Rankings of research universities. Refer to the...Ch. 11.3 - Life tests of cutting tools. To Improve the...Ch. 11.4 - Construct both a 95% and a 90% confidence interval...Ch. 11.4 - Consider the following pairs of observations: a....Ch. 11.4 - Refer to Exercise 11.46. Construct an 80% and a...Ch. 11.4 - Do the accompanying data provide sufficient...Ch. 11.4 - State Math SAT Scores. Refer to the SPSS simple...Ch. 11.4 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.4 - Prob. 11.51ACBCh. 11.4 - Prob. 11.52ACBCh. 11.4 - Estimating repair and replacement costs of water...Ch. 11.4 - Prob. 11.54ACBCh. 11.4 - Prob. 11.55ACICh. 11.4 - Beauty and electoral success. Are good looks an...Ch. 11.4 - Prob. 11.57ACICh. 11.4 - Prob. 11.58ACICh. 11.4 - Prob. 11.59ACICh. 11.4 - Prob. 11.60ACICh. 11.4 - Rankings of research universities. Refer to the...Ch. 11.4 - Prob. 11.62ACACh. 11.4 - Does elevation impact hitting performance in...Ch. 11.5 - Explain what each of the following sample...Ch. 11.5 - Describe the slope of the least squares line if a....Ch. 11.5 - Construct a scatterplot for each data set. Then...Ch. 11.5 - Calculate r2 for the least squares line in each of...Ch. 11.5 - Use the applet Correlation by Eye to explore the...Ch. 11.5 - In business, do nice guys finish first or last?...Ch. 11.5 - Going for it on fourth-down in the NFL Each week...Ch. 11.5 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.5 - RateMyProfessors.com. A popular Web site among...Ch. 11.5 - Last name and acquisition timing. Refer to the...Ch. 11.5 - Women in top management. An empirical analysis of...Ch. 11.5 - Prob. 11.74ACICh. 11.5 - Prob. 11.75ACICh. 11.5 - Prob. 11.76ACICh. 11.5 - Prob. 11.77ACICh. 11.5 - Prob. 11.78ACICh. 11.5 - Evaluation of an imputation method for missing...Ch. 11.5 - Prob. 11.80ACICh. 11.5 - Prob. 11.81ACACh. 11.6 - Consider the followings of measurements: a...Ch. 11.6 - Consider the pairs of measurements shown in the...Ch. 11.6 - In fitting a least squares line to n = 10 data...Ch. 11.6 - Prob. 11.86ACBCh. 11.6 - Prob. 11.87ACBCh. 11.6 - Prob. 11.88ACBCh. 11.6 - Prob. 11.89ACBCh. 11.6 - Prob. 11.90ACBCh. 11.6 - Prob. 11.91ACICh. 11.6 - Ranking driving performance of professional...Ch. 11.6 - Spreading rate of spilled liquid Refer to the...Ch. 11.6 - Removing nitrogen from toxic wastewater. Highly...Ch. 11.6 - Predicting quit rates In manufacturing The reasons...Ch. 11.6 - Life tests of cutting tools Refer to the data...Ch. 11.7 - Prices of recycled materials. Prices of recycled...Ch. 11.7 - Thickness of dust on solar cells. The performance...Ch. 11.7 - Management research In Africa. The editors of the...Ch. 11.7 - An MBAs work-life balance. The importance of...Ch. 11 - In fitting a least squares line ton= 15 data...Ch. 11 - Consider the following sample data. a. Construct a...Ch. 11 - Consider the following 10 data points. a. Plot the...Ch. 11 - Drug controlled-release rate study. The effect of...Ch. 11 - Metaskills and career management. Effective...Ch. 11 - Burnout of human services professionals. Emotional...Ch. 11 - Retaliation against company whistle-blowers....Ch. 11 - Extending the life of an aluminum smelter pot. An...Ch. 11 - Diamonds sold at retail. Refer to the Journal of...Ch. 11 - Sports news on local TV broadcasts. The Sports...Ch. 11 - Evaluating managerial success. An observational...Ch. 11 - Doctors and ethics. Refer to the Journal of...Ch. 11 - FCAT scores and poverty. In the state of Florida,...Ch. 11 - Monetary values of NFL teams. Refer to the Forbes...Ch. 11 - Evaluating a truck weigh-in-motion program. The...Ch. 11 - Energy efficiency of buildings. Firms conscious of...Ch. 11 - Forecasting managerial needs. Managers are an...Ch. 11 - Prob. 11.118ACACh. 11 - Prob. 11.119CTCCh. 11 - Prob. 11.120CTC
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- 4. Consider the following regression equation, where Google is equal to 1 if an individual in thesample has worked at Google and 0 otherwise, and Earnings is annual earnings in thousands ofpounds (standard errors in parentheses):Earnings \ = 25000(12.5)+ 42000(7.0)Google,(a) Interpret the coefficient on Google.(b) Is the coefficient on Google statistically significant at the 5% level? How do you know?(c) Suppose that instead of Google we had used a variable called NeverGoogle, equal to 1 if anindividual has never worked at Google and 0 otherwise. (i) How would the slope coefficientchange? (ii) What would happen to the intercept? (d) What prevents us from interpreting the coefficient on Google as a causal effect? Give examplesin your answer.arrow_forward4. Examine the regression table below before answering the questions that follow.Throughout, the Log() function represents the natural logarithm, so that Log(e) =1:Dependent Variable: Log(Expenditures on Cigarettes + 1)Method: Least SquaresVariable Coefficient Std. ErrorConstant 0.50 0.41Log(Income+1) −0.02 0.002(a) Why are the dependent and explanatory variables in the form log(1+x), ratherthan log(x)? (b) Which of the above coefficients are statistically significant? How do you know?(c) Interpret the coefficient on Log(Income+1). (d) What is the predicted level of Log(Expenditures on Cigarettes + 1) for anobserved individual with income of e10 − 1? (4arrow_forward3. Consider the following three (fictional) data points:Country Ultima Thule Narnia NeverlandGDP per capita (US $, 2021, in thousands) 10 30 20Deaths from COVID-19 as of Jan. 2023, millions 0.24 0.16 0.05(a) What is the slope of the line of best fit through these three points, whereDeaths from COVID-19 is the dependent variable and GDP per capita is theexplanatory variable? (b) The standard error for the slope parameter is 0.009. What does this standarderror measure? (c) Is the slope parameter statistically significant at the 5% level of significance?(The relevant critical value is not the usual value, but 4.303, due to the tinysample size). Explain what this means. (d) Why might this slope parameter be a misleading indicator of the relationshipbetween these two variables?arrow_forward
- Consider the following estimated regression equation, where both Rent and Earnings aremeasured in pounds (£) at the individual level (standard errors in parentheses):log(\Rent) = 6.9(0.69)+ 0.9(0.3)log(Earnings),(a) Interpret the coefficient on log(Earnings). (b) If we divided Earnings by 1000, so that it is measured in 1000s of pounds instead of pounds,how would (i) the slope, (ii) the intercept change in the above equation? Now suppose the variable London is added, which is equal to one if an individual iives inLondon, and zero otherwise. The estimated regression equation changes to:log(\Rent) = 6.22(0.622)+ 0.5(0.05)log(Earnings) + 2(0.5)London,(c) Interpret the coefficient on London. (d) Explain why the coefficient on log(Earnings) when London is included in the regression andthe coefficient on log(Earnings) when London is not included in the regression are not thesame.arrow_forward3. Consider the following regression equation, where Cigs is daily spending on cigarettes in poundssterling (£), Y earsEduc is years of education, and F emale equals one if an individual is femaleand zero otherwise (standard errors in parentheses):Cigs [ = 4(1.6)− 0.08(0.032)Y earsEduc − 0.5(0.2)F emale,(a) Interpret the coefficients on Y earsEduc and F emale. (b) What does the model predict the average daily spending on cigarettes would be for womenwith 12 years of education? (c) Form the 95% confidence interval for the coefficient on F emale. (d) Economists are often interested in estimating production functions of the Cobb-Douglas form(Yiis the ith firm’s output, Liits spending on labour, and Kiits spending on capital):Yi = ALαi Kβi,How might someone estimate α and β from this equation using linear regression?arrow_forward2. The demand and supply functions for two interdependent goods X and Y are givenbyQDX = 7 − 4PX + 2PYQSX = −6 + 4PX − PYQDY = 1 + PX − PYQSY = −4 − PX + 2PY(a) Find the market equilibrium condition for each good. (b) Express the equilibrium conditions in the matrix form Ax = b.(c) Find the inverse of matrix A. (d) Given your result in part (c), calculate the equilibrium prices. (e) What is the equilibrium quantity for goods X and Y ?arrow_forward
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- Which of the following graphs best represents the production possibility frontier of Country Y (Line Y), the production possibility frontier of Country Z (Line Z), and the production possibility frontier of this whole economy (Line W)? (Hint: Find W by adding the productive capabilities of Country Y and Z) Group of answer choicesarrow_forwardWhich of the following factors tend to decrease the wage differential between union and non union workers: unions tend to organize the firms with the lowest ability to pay initially all of the above unions must moderate their wage demand to keep workers competitive some nonunion employers pay their employees above union wages only ‘a’ and ‘b’ abovearrow_forwardThe accompanying graph shows the short-run demand and cost situation for a price searcher in a market with low barriers to entry. Price (dollars) 24 8 MC ATC MR 30 D 45 50 Quantity/time The firm will maximize its profit at a quantity of units. After choosing the profit maximizing quantity, the firm will charge a price of The firm will receive $ in revenue at the profit-maximizing quantity. The total cost of production for this profit-maximizing quantity is S The maximum profit the firm can earn in this situation is $ per unit for this output. How will the situation change over time? Profits will attract rival firms into the market until the profit-maximizing price falls to the level of per-unit cost. ◇ Losses will induce firms to leave this market until the profit maximizing price falls to zero. The market will adjust until the price charged by this firm no longer exceeds marginal cost at the profit-maximizing quantity. This market is already in long-run equilibrium, and will not…arrow_forward
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