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- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?Use Excels functions (not @RISK) to generate 1000 random numbers from a normal distribution with mean 100 and standard deviation 10. Then freeze these random numbers. a. Calculate the mean and standard deviation of these random numbers. Are they approximately what you would expect? b. What fraction of these random numbers are within k standard deviations of the mean? Answer for k = 1; for k = 2; for k = 3. Are the answers close to what they should be (about 68% for k = 1, about 95% for k = 2, and over 99% for k = 3)? c. Create a histogram of the random numbers using about 10 bins of your choice. Does this histogram have approximately the shape you would expect?The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
- The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What does the accuracy rate indicate? Metrics Metric Value Accuracy (#correct) 178 Accuracy (%correct) 85.6 Specificity 0.88219 Sensitivity (Recall) 0.6 Precision 0.82400 F1 Score 0.88213 Success Class 1 Success Probability 0.4 Multiple Choice 85.6% of the population has purchased a virtual assistant. 60% of the observations are correctly classified. 85.6% of the observations are correctly classified. 14.4% of the observations are correctly classified. Explain all the incorrect answers alsoLet’s suppose that you have a set of time-series variables, and you want to model the relationship between them. Read the situations given below and answer the questions. (200 words)a) Explain the statistical test if the linear combination (of time-series variables) is I(0).b) Which statistical test can be applied if all the series are integrated of the same order I(1). Justify your answerExplain or define each of these terms:a. Laplace criterionb. Minimax regretc. Expected valued. Expected value of perfect information
- As employees leave a company, they are asked to rate their level of job satisfaction during the time they were employed by the company. A sample set of scores (out of a maximum of 10) is provided below. 3 6 4 4 5 2 1 3 2 5 3 7 2 2 3 1 9 1 Use the information provided in the table to calculate: The median; The mode; The mean; The lower quartile (Q1); The upper quartile (Q3); The interquartile range (IQR); The standard deviation. State whether or not the ex-employees were likely to have left the company as a result of lack of job satisfaction. Use the statistics above to justify your conclusion. Discuss in which ways the company could benefit from making these statistics available to its current employees.Two machines are currently in use in a process atthe Dennis Kira Mfg. Co. The standards for this process areLSL = .40011 and USL = .40311• Machine One is currently producingwith mean = .401 II and standard deviation .000411• Machine ..)Two is currently producing with mean .401511 and standard deviation.000511• Which machine has the higher capability index?Given the attached data. Answer the following questions for a 7 period moving average. t At 1 5477 2 3338 3 4799 4 2852 5 6332 6 8385 7 4382 8 4184 9 14229 10 10385 11 11676 12 5271 13 8938 14 9279 15 13990 16 2890 17 13027 18 8970 19 6700 20 7065 21 12491 22 8748 23 8396 24 6102 25 7559 26 7997 27 11981 28 10680 29 5783 30 2501 31 7620 32 10194 33 7908 34 11985 35 5863 36 3024 37 8758 38 1640 39 6569 40 11728 41 6659 42 2830 43 10018 44 8448 45 12409 46 2083 47 6374 48 7438 49 4576 50 4795 MAD = Average(|A-F|) TS =SUM(A-F)/MAD MSE = Average(A-F)2 1. Compute your forecast for period 51. The potential answers are: A: 11221.6 units. B: 12461 units. C: 8020.83 units. D: 4414 units. E: 6589 units.
- An advertising executive claims that there is a difference in the mean household income for credit cardholders of Visa Gold and of MasterCard Gold. A random survey of 15 Visa Gold cardholders resulted in a mean household income of $68,420 with a standard deviation of $9100. A random survey of 6 MasterCard Gold cardholders resulted in a mean household income of $59,200 with a standard deviation of $9200. Is there enough evidence to support the executive's claim? Let μ1 be the true mean household income for Visa Gold cardholders and μ2 be the true mean household income for MasterCard Gold cardholders. Use a significance level of α=0.05 for the test. Assume that the population variances are not equal and that the two populations are normally distributed. Step 1 of 4: State the null and alternative hypotheses for the test. Step 2 of 4: Compute the value of the t test statistic. Round your answer to three decimal places. Step 3 of 4: Determine the decision rule for rejecting the…. Alexandera is the Research manager with Freezemore Appliances. Freezemore has bee receiving a LOT of complaints with one of it’s most popular refrigerators. The refrigerator freezes everything in both the freezer and the refrigerator freeing everything inside. The vice president of marketing told Alexandra that “we need to quickly discover how to turn this problem into a desirable situation. You need to determine the underlying cause of the problem and perhaps even make improvements to the freezer.” When Alexandra analyzes the underlying causes of the freezing problem, which function is she performing? a. analytics b. feasibility c. MBO d.synergy e. diagnosisThe data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1012 872 895 1078 1235 1172 Temperature (°F) 81.9 76.3 78.4 84 87.2 88.4 What is the regression equation? y= +. x What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best-predicted temperature when a bug is chirping at 3000 chirps per minute is ? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…