You have just run a regression of monthly returns on MAD, a newspaper and magazine publisher, against returns on the S&P 500, and arrived at the following result.
Intercept: -0.005% ; Slope: 1.950; R2: 45. 0%.
You now realize that MAD went through a major restructuring at the end of last month (which was the last month of your regression), and made the following changes.
• The firm sold off its magazine division, which had an unlevered beta of 0.55, for 39 million.
• It borrowed an additional 18 million and bought back stock worth 57 million. After the sale of the division and the share repurchase, MAD had 43 million in debt and 148 million in equity outstanding. If the firm’s tax rate is 40.00% percent, re-estimate the beta after these changes.
1.
HomeworkUnanswered
The value of equity before the sale of the division and stock buyback is equal to: (please enter your numbers in millions (i.e., 100 million is 100, not 100,000,000)
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2
HomeworkUnanswered
The value of debt before the sale of the division and stock buyback is equal to
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3
HomeworkUnanswered
The unlevered beta of the firm prior to the sale of the division and stock buyback is equal to
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Numeric Answer
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4
HomeworkUnanswered
The weight (proportion of selling unit divided by total firm value) of the selling unit is equal to (hint: please enter your answer in decimal format. i.e., 25% is 0.25)
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5
HomeworkUnanswered
The weight of the remaining unit is equal to
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6
HomeworkUnanswered
The unlevered beta of the remaining unit is equal to
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7
HomeworkUnanswered
The levered beta after the sale of the division and stock buyback is equal to
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In: Accounting
For a new study conducted by a fitness magazine,285 females were randomly selected. For each, the mean daily calorie consumption was calculated for a September-February period. A second sample of 275 females was chosen independently of the first. For each of them, the mean daily calorie consumption was calculated for a March-August period. During the September-February period, participants consumed a mean of 2383.5 calories daily with a standard deviation of 208. During the March-August period, participants consumed a mean of 2416.5 calories daily with a standard deviation of 262.5 . The population standard deviations of daily calories consumed for females in the two periods can be estimated using the sample standard deviations, as the samples that were used to compute them were quite large. Construct a 95% confidence interval for µ1-µ2 , the difference between the mean daily calorie consumption µ1 of females in September-February and the mean daily calorie consumption µ2 of females in March-August. Then complete the table below.
Carry your intermediate computations to at least three decimal places. Round your answers to at least two decimal places.
| What is the lower limit of the 95% confidence interval? |
| What is the upper limit of the 95% confidence interval? |
In: Statistics and Probability
1) A leading magazine (like Barron's) reported at one time that the average number of weeks an individual is unemployed is 15.8 weeks. Assume that for the population of all unemployed individuals the population mean length of unemployment is 15.8 weeks and that the population standard deviation is 9.5 weeks. Suppose you would like to select a random sample of 22 unemployed individuals for a follow-up study.
Find the probability that a single randomly selected value is between 19 and 20.7. P(19 < X < 20.7) =
Find the probability that a sample of size n = 22 n = 22 is randomly selected with a mean between 19 and 20.7. P(19 < M < 20.7) =
2)CNNBC recently reported that the mean annual cost of auto
insurance is 995 dollars. Assume the standard deviation is 146
dollars. You will use a simple random sample of 138 auto insurance
policies.
Find the probability that a single randomly selected policy has a
mean value between 960.2 and 976.4 dollars.
P(960.2 < X < 976.4) =
Find the probability that a random sample of size n=138n=138 has a
mean value between 960.2 and 976.4 dollars.
P(960.2 < M < 976.4) =
Enter your answers as numbers accurate to 4 decimal places.
In: Statistics and Probability
An expert who works for a car magazine obtained random data (rounded to the nearest thousand) among two categories of used or new cars:
Domestic
Foreign
The expert would like to understand sales based on list price (rounded to the nearest thousand dollars), sale price (rounded to the nearest thousand dollars), and number of days it takes to sell each car. The complete data set is in the file named Cars.
Managerial Report
Prepare a report (see below) that summarizes your assessment of the nature of the car market. Be sure to include the following seven items in your report.
1 Descriptive statistics (mean, median, range, standard deviation, and coefficient of variation) to summarize each of the three variables for the all Domestic cars. Use z-scores to determine if there any outliers in the data set for any of the three variables. If there are any outliers in any category, please list them and state for which category they are an outlier. If a result is an outlier, state whether it is below or above the mean.
2 Descriptive statistics (mean, median, range, standard deviation, and coefficient of variation) to summarize each of the three variables for the all Foreign cars. Use z-scores to determine if there any outliers in the data set for any of the three variables. If there are any outliers in any category, please list them and state for which category they are an outlier. If a result is an outlier, state whether it is below or above the mean.
3 Compare your summary results from #1 and #2. Discuss any specific statistical results that would help the car expert understand the car market.
4 Develop a 98% confidence interval estimate of the population mean sales price and population mean number of days to sell for Domestic cars. What is the Margin of error? What are the lower (or left) and upper (or right) endpoints of the confidence interval? Interpret your results.
5 Develop a 98% confidence interval estimate of the population mean sales price and population mean number of days to sell for Foreign cars. What is the Margin of error? What are the lower (or left) and upper (or right) endpoints of the confidence interval? Interpret your results.
6 Assume the car expert requested estimates of the mean number of days to sell for the Domestic cars with a margin of error of seven days and the mean number of days of Foreign cars with a margin of error of eight days. Using 98% confidence, how large should the sample sizes be for each?
7 Suppose a Domestic car has a list price of $30,000 and a Foreign car has a list price of $30,000. What is your estimate of the final selling price (based on the percent difference for the sale and list price) and number of days required to sell each of these cars?
| Domestic Cars | Foreign Cars | ||||||
| Car | List Price in K | Sale Price in K | Days to Sell | List Price in K | Sale Price in K | Days to Sell | |
| 1 | 6.1 | 4.4 | 36 | 83.1 | 78.5 | 101 | |
| 2 | 67.6 | 66.8 | 51 | 59.6 | 57.1 | 62 | |
| 3 | 14 | 13.4 | 87 | 37 | 32.5 | 63 | |
| 4 | 83.4 | 80.5 | 80 | 43.4 | 43.2 | 47 | |
| 5 | 40 | 35.4 | 38 | 16.3 | 15 | 93 | |
| 6 | 56 | 52 | 24 | 8.3 | 5.9 | 21 | |
| 7 | 71.2 | 68.7 | 27 | 29.2 | 27.5 | 107 | |
| 8 | 50.7 | 49.7 | 52 | 32.7 | 32.7 | 15 | |
| 9 | 4.9 | 4.3 | 74 | 23.9 | 23.5 | 12 | |
| 10 | 70.5 | 66.5 | 84 | 85.5 | 85.1 | 58 | |
| 11 | 58 | 56 | 30 | 19 | 16.3 | 96 | |
| 12 | 75 | 73.7 | 31 | 19 | 18.9 | 106 | |
| 13 | 2.8 | 1.1 | 88 | 80.8 | 77.4 | 50 | |
| 14 | 7.7 | 4 | 11 | 17.7 | 15.6 | 42 | |
| 15 | 20 | 16.2 | 20 | 71.4 | 70.4 | 75 | |
| 16 | 23 | 21.5 | 71 | 16.1 | 13.8 | 62 | |
| 17 | 6.2 | 6 | 88 | 49.2 | 45.2 | 91 | |
| 18 | 18 | 14 | 43 | 40 | 38 | 6 | |
| 19 | 97 | 93.2 | 95 | 32 | 29.2 | 52 | |
| 20 | 69.2 | 66.8 | 37 | 27.2 | 22.5 | 71 | |
| 21 | 63.5 | 60.7 | 13 | 85.5 | 82.8 | 106 | |
| 22 | 65 | 61.9 | 60 | 87.4 | 85.7 | 91 | |
| 23 | 9.9 | 7 | 24 | 58.9 | 56.9 | 83 | |
| 24 | 90.2 | 88.3 | 42 | 56.2 | 52.8 | 29 | |
| 25 | 56 | 55 | 91 | 13.5 | 10 | 76 | |
| 26 | 80 | 75.2 | 39 | 55.7 | 54.2 | 40 | |
| 27 | 58.7 | 58.3 | 58 | 75.7 | 74.6 | 47 | |
| 28 | 33.1 | 32.9 | 47 | 89.1 | 85.7 | 67 | |
| 29 | 31.5 | 28.7 | 86 | 3.5 | 3.2 | 106 | |
| 30 | 54.5 | 54.1 | 88 | 67.5 | 65.3 | 100 | |
| 31 | 22.4 | 17.8 | 30 | 41.4 | 40.1 | 10 | |
| 32 | 40.3 | 38.4 | 29 | 45.3 | 43.3 | 36 | |
| 33 | 27.2 | 22.6 | 34 | 87.2 | 85.1 | 61 | |
| 34 | 14.4 | 14.1 | 12 | 16.4 | 14.3 | 65 | |
| 35 | 5.6 | 1.5 | 86 | 32.6 | 29.1 | 25 | |
| 36 | 42.2 | 40.8 | 72 | 14.2 | 14.2 | 39 | |
| 37 | 9.5 | 6.2 | 69 | 60.5 | 59.1 | 79 | |
| 38 | 93.1 | 90.5 | 32 | 73.1 | 68.3 | 83 | |
| 39 | 10.7 | 7.3 | 15 | 48.7 | 44.7 | 65 | |
| 40 | 93.3 | 91.7 | 15 | 38.3 | 38.2 | 35 | |
| 41 | 50 | 49.1 | 19 | 6.6 | 4.3 | 6 | |
| 42 | 33.2 | 29.6 | 27 | 86.2 | 81.4 | 53 | |
| 43 | 67 | 60 | 18 | 5 | 4.6 | 108 | |
| 44 | 56 | 53.1 | 54 | 37 | 32.7 | 85 | |
| 45 | 49.5 | 48.2 | 37 | 23.5 | 21.2 | 32 | |
| 46 | 52.7 | 48.8 | 66 | 90.7 | 87.4 | 97 | |
| 47 | 41.1 | 39.7 | 78 | 84.1 | 83.8 | 16 | |
| 48 | 72.1 | 70.9 | 12 | 45.1 | 42.7 | 38 | |
| 49 | 50 | 46.9 | 84 | 51.7 | 49.9 | 53 | |
| 50 | 88 | 84.2 | 20 | 36 | 34.6 | 97 | |
| 51 | 11.8 | 11.3 | 20 | 66.8 | 65 | 45 | |
| 52 | 69.5 | 69 | 90 | 54.5 | 50.2 | 31 | |
| 53 | 63 | 62.6 | 35 | 33 | 33 | 44 | |
| 54 | 60 | 58.1 | 46 | 11.4 | 10.8 | 92 | |
| 55 | 66.7 | 66.1 | 47 | 59.7 | 57.9 | 49 | |
| 56 | 58 | 55.5 | 51 | 84.2 | 80.1 | 52 | |
| 57 | 67.2 | 62.7 | 96 | 48.2 | 43.4 | 101 | |
| 58 | 74.9 | 70.4 | 59 | 68.9 | 64.9 | 14 | |
| 59 | 71.4 | 70.2 | 14 | 60.4 | 59.9 | 98 | |
| 60 | 71.1 | 67.8 | 75 | 87.1 | 85.1 | 90 | |
| 61 | 54 | 54 | 52 | 68.3 | 66.4 | 61 | |
| 62 | 19.9 | 17.2 | 60 | 8.9 | 7.5 | 32 | |
| 63 | 49.5 | 48.6 | 56 | 39.5 | 39.3 | 48 | |
| 64 | 56.8 | 54.8 | 11 | 57.8 | 53.1 | 29 | |
| 65 | 74 | 71.3 | 71 | 59 | 57.5 | 98 | |
| 66 | 20.4 | 17 | 31 | 22.4 | 19.4 | 6 | |
| 67 | 34.5 | 32.5 | 40 | 78.5 | 77.3 | 6 | |
| 68 | 17.2 | 14.4 | 29 | 11.2 | 9.4 | 83 | |
| 69 | 45 | 42.5 | 72 | 86.2 | 82 | 79 | |
| 70 | 82 | 81 | 32 | 4 | 3.5 | 70 | |
| 71 | 40 | 39.3 | 21 | 22.6 | 21.1 | 38 | |
| 72 | 16 | 12.4 | 62 | 36 | 36 | 18 | |
| 73 | 25 | 20.1 | 72 | 88 | 87.1 | 26 | |
| 74 | 64.1 | 61.5 | 10 | 88.1 | 85.2 | 41 | |
| 75 | 39.5 | 35.4 | 71 | 66.5 | 61.8 | 100 | |
| 76 | 72 | 67.3 | 97 | 4.1 | 3.1 | 7 | |
| 77 | 13 | 10.4 | 80 | 22 | 20.6 | 11 | |
| 78 | 37.1 | 36.1 | 26 | 71.1 | 70.5 | 33 | |
| 79 | 67.7 | 62.7 | 29 | 36.7 | 33.5 | 42 | |
| 80 | 40 | 36.6 | 28 | 69.2 | 66.3 | 9 | |
| 81 | 55.9 | 52.8 | 71 | 14.9 | 12.6 | 94 | |
| 82 | 51 | 47.4 | 81 | 81 | 78.8 | 104 | |
| 83 | 50 | 45.4 | 41 | 46.9 | 44.3 | 25 | |
| 84 | 44.2 | 41 | 15 | 11.2 | 6.6 | 69 | |
| 85 | 12 | 9.8 | 31 | 7 | 5.3 | 66 | |
| 86 | 72 | 70 | 78 | 36 | 31.9 | 52 | |
| 87 | 51.6 | 46.6 | 84 | 49.6 | 46.8 | 39 | |
| 88 | 54.4 | 52.6 | 26 | 42.4 | 38.3 | 92 | |
| 89 | 44.5 | 42.5 | 92 | 4.5 | 4 | 46 | |
| 90 | 61.6 | 60.9 | 19 | 31.6 | 31 | 64 | |
| 91 | 34.1 | 33.1 | 91 | 57.1 | 53.3 | 38 | |
| 92 | 80 | 79 | 38 | 42 | 39 | 64 | |
| 93 | 61.9 | 61.1 | 85 | 71.9 | 71 | 11 | |
| 94 | 74.6 | 73.4 | 84 | 86.6 | 86.5 | 11 | |
| 95 | 17 | 14.5 | 90 | 90 | 87.2 | 6 | |
| 96 | 10.8 | 7.9 | 70 | 47.8 | 42.9 | 73 | |
| 97 | 44.7 | 43.8 | 61 | 52.7 | 52.6 | 66 | |
| 98 | 11.7 | 10.3 | 73 | 35.7 | 32 | 31 | |
| 99 | 97.9 | 95.9 | 92 | 44.9 | 43.3 | 24 | |
| 100 | 67.5 | 63 | 10 | 21.5 | 19.4 | 89 | |
| 101 | 64 | 61.9 | 43 | 84.3 | 83.2 | 31 | |
| 102 | 97.7 | 93.7 | 73 | 69.7 | 65.7 | 100 | |
| 103 | 8.9 | 6.5 | 87 | 37.9 | 37.9 | 43 | |
| 104 | 51.3 | 47.7 | 18 | 49.3 | 45.5 | 18 | |
| 105 | 56 | 53.1 | 47 | 82.7 | 82.5 | 67 | |
| 106 | 12.6 | 8.4 | 95 | 3.6 | 3.2 | 7 | |
| 107 | 42.6 | 38.7 | 73 | 53.6 | 48.9 | 87 | |
| 108 | 50 | 47.7 | 84 | 74.2 | 69.2 | 11 | |
| 109 | 25.7 | 24.8 | 38 | 56.7 | 53.2 | 50 | |
| 110 | 72.4 | 67.6 | 98 | 54.4 | 51 | 69 | |
| 111 | 20.7 | 18.3 | 16 | 38.7 | 34 | 28 | |
| 112 | 62.3 | 57.9 | 13 | 4.3 | 2.9 | 85 | |
| 113 | 41.4 | 37.4 | 61 | 19.4 | 15.9 | 7 | |
| 114 | 50 | 49 | 97 | 16.5 | 12.8 | 95 | |
| 115 | 77.9 | 76.7 | 84 | 41.9 | 41 | 52 | |
| 116 | 10 | 9.2 | 25 | 73 | 69.4 | 98 | |
| 117 | 80 | 76.1 | 44 | 56 | 55.9 | 68 | |
| 118 | 61.5 | 60 | 48 | 69.5 | 68.9 | 43 | |
| 119 | 61.1 | 58.3 | 73 | 36.1 | 32.4 | 85 | |
| 120 | 38.6 | 34.2 | 54 | 32.6 | 28 | 7 | |
| 121 | 73.9 | 68.9 | 39 | 85.9 | 80.9 | 63 | |
| 122 | 30 | 30 | 94 | 68.9 | 68.8 | 26 | |
| 123 | 56 | 51.3 | 17 | 81.3 | 78.6 | 53 | |
| 124 | 39 | 36.1 | 72 | 52 | 50.4 | 104 | |
| 125 | 7.4 | 3.5 | 81 | 60.4 | 58.2 | 67 | |
| 126 | 74.9 | 74.5 | 16 | 23.9 | 19.4 | 43 | |
| 127 | 40 | 37.9 | 43 | 59.6 | 55.8 | 28 | |
| 128 | 43 | 39 | 23 | 44.5 | 44.3 | 54 | |
| 129 | 28.8 | 24.6 | 67 | 90.8 | 88.8 | 67 | |
| 130 | 14.5 | 10.5 | 14 | 66.5 | 63.5 | 11 | |
| 131 | 10.8 | 9.9 | 59 | 60.8 | 56 | 19 | |
| 132 | 6.6 | 1.9 | 12 | 83.6 | 82.5 | 8 | |
| 133 | 12.6 | 10.7 | 51 | 35.6 | 33.7 | 41 | |
| 134 | 3.4 | 0.2 | 86 | 81.4 | 78.5 | 45 | |
| 135 | 40.6 | 40.6 | 30 | 8.6 | 3.7 | 12 | |
| 136 | 67 | 63.5 | 70 | 7.2 | 6.3 | 35 | |
| 137 | 33.6 | 32 | 97 | 80.6 | 75.7 | 44 | |
| 138 | 67 | 66 | 59 | 3.5 | 3.2 | 84 | |
| 139 | 14 | 9.5 | 94 | 52 | 49.4 | 24 | |
| 140 | 22.7 | 19.7 | 34 | 6.7 | 2.7 | 18 | |
| 141 | 69.6 | 65.6 | 26 | 54.6 | 49.6 | 65 | |
| 142 | 68.7 | 65.2 | 38 | 11.7 | 8.5 | 13 | |
| 143 | 70 | 68 | 95 | 84.7 | 82.7 | 83 | |
| 144 | 57 | 54 | 89 | 57.9 | 57.1 | 103 | |
| 145 | 56.6 | 54.6 | 89 | 22.6 | 18.3 | 97 | |
| 146 | 69.4 | 69.2 | 80 | 85.4 | 80.9 | 77 | |
| 147 | 81.7 | 77.3 | 86 | 72.7 | 70.8 | 22 | |
| 148 | 70 | 65.8 | 72 | 30.3 | 28.5 | 57 | |
| 149 | 39.3 | 37.2 | 52 | 10.3 | 6.2 | 108 | |
| 150 | 16.8 | 13.3 | 49 | 80.8 | 80.1 | 11 | |
| 151 | 65.3 | 62.5 | 19 | 64.3 | 59.6 | 100 | |
| 152 | 15.9 | 14 | 91 | 31.9 | 29 | 84 | |
| 153 | 57.5 | 54.8 | 72 | 70.5 | 66.5 | 45 | |
| 154 | 55.7 | 55 | 61 | 7.7 | 5.7 | 71 | |
| 155 | 67.3 | 63.5 | 39 | 20.3 | 16.5 | 54 | |
| 156 | 10 | 9.6 | 72 | 56 | 52.3 | 77 | |
| 157 | 96 | 94.1 | 81 | 6 | 2.1 | 46 | |
| 158 | 57.7 | 55.7 | 22 | 24.7 | 23.7 | 75 | |
| 159 | 15.7 | 15.2 | 77 | 59.7 | 55.4 | 35 | |
| 160 | 12.2 | 7.8 | 94 | 53.2 | 48.8 | 13 | |
| 161 | 56.1 | 52.5 | 58 | 48.1 | 47.8 | 24 | |
| 162 | 10.3 | 9.6 | 36 | 19.3 | 16.3 | 64 | |
| 163 | 58 | 54.7 | 98 | 6.3 | 3.5 | 61 | |
| 164 | 7.5 | 6.5 | 59 | 26.5 | 22 | 84 | |
| 165 | 14.4 | 12.8 | 62 | 44.4 | 43.7 | 59 | |
| 166 | 57.5 | 57.4 | 46 | 89.5 | 89.2 | 36 | |
| 167 | 40.1 | 39.7 | 68 | 69.1 | 67.5 | 49 | |
| 168 | 23.3 | 21 | 33 | 48.3 | 44.7 | 103 | |
| 169 | 59 | 57.9 | 53 | 89 | 84.4 | 108 | |
| 170 | 24.2 | 19.3 | 33 | 56.2 | 54.6 | 20 | |
| 171 | 62 | 59.2 | 22 | 30 | 25.1 | 67 | |
| 172 | 45 | 40.7 | 37 | 57.8 | 56.3 | 42 | |
| 173 | 42 | 42 | 33 | 70.4 | 68.5 | 16 | |
| 174 | 60 | 59.5 | 54 | 50.1 | 46.5 | 43 | |
| 175 | 77.8 | 75 | 32 | 18.8 | 15.9 | 63 | |
| 176 | 73 | 70 | 76 | 24 | 22.2 | 103 | |
| 177 | 13.4 | 12 | 53 | 38.4 | 35.5 | 16 | |
| 178 | 29 | 27.9 | 57 | 73.6 | 71.5 | 93 | |
| 179 | 97 | 92.7 | 31 | 25 | 24.7 | 60 | |
| 180 | 10 | 7.7 | 62 | 19 | 18.5 | 70 | |
| 181 | 21.7 | 19.5 | 13 | 49.7 | 49.6 | 47 | |
| 182 | 42.9 | 41.1 | 69 | 67.9 | 63.2 | 107 | |
| 183 | 23 | 20 | 42 | 28.6 | 28.3 | 50 | |
| 184 | 35 | 34.7 | 15 | 26.7 | 24.2 | 40 | |
| 185 | 3.4 | 3.3 | 34 | 51.4 | 47 | 25 | |
| 186 | 45 | 40.6 | 72 | 53.5 | 53.1 | 99 | |
| 187 | 7.9 | 4.6 | 50 | 6.9 | 2.2 | 23 | |
| 188 | 44 | 41.2 | 63 | 9.1 | 6.2 | 97 | |
| 189 | 8 | 3.1 | 36 | 70 | 68.3 | 83 | |
| 190 | 33 | 31.9 | 27 | 17 | 13 | 106 | |
| 191 | 2.6 | 2.4 | 63 | 57.6 | 55.6 | 87 | |
| 192 | 24 | 23 | 63 | 19.2 | 17.8 | 52 | |
| 193 | 23.6 | 19.7 | 30 | 34.6 | 32.2 | 46 | |
| 194 | 49.1 | 45.3 | 67 | 57.1 | 54.2 | 37 | |
| 195 | 1.5 | 1.3 | 69 | 80.5 | 80.4 | 98 | |
| 196 | 57.4 | 52.8 | 89 | 81.4 | 80.4 | 108 | |
| 197 | 60.9 | 59.8 | 56 | 69.9 | 69 | 88 | |
| 198 | 59.7 | 56.1 | 65 | 16.7 | 14.9 | 106 | |
| 199 | 1.8 | 1.7 | 20 | 78.8 | 75.4 | 7 | |
| 200 | 63.1 | 61.7 | 40 | 54.1 | 52.2 | 57 | |
In: Statistics and Probability
For a new study conducted by a fitness magazine, 270 females were randomly selected. For each, the mean daily calorie consumption was calculated for a September-February period. A second sample of 285 females was chosen independently of the first. For each of them, the mean daily calorie consumption was calculated for a March-August period. During the September-February period, participants consumed a mean of 2387.2 calories daily with a standard deviation of 216. During the March-August period, participants consumed a mean of 2412.8 calories daily with a standard deviation of 255. The population standard deviations of daily calories consumed for females in the two periods can be estimated using the sample standard deviations, as the samples that were used to compute them were quite large. Construct a 90% confidence interval for −μ1μ2, the difference between the mean daily calorie consumption μ1 of females in September-February and the mean daily calorie consumption μ2 of females in March-August. Then complete the table below.Carry your intermediate computations to at least three decimal places. Round your answers to at least two decimal places. (If necessary, consult a list of formulas.)
|
||||
In: Statistics and Probability
Case study: Keeping Your Eye on the Ball
We sometimes read a newspaper or magazine or listen to a news report and hear about the downfall of U.S. manufacturing and how many people are losing their jobs in manufacturing plants. It sounds depressing but the question is, “Has the United States really fallen that far behind other countries in manufacturing capability?” The answer is no, and this video is meant to highlight just one example of a successful manufacturing company. There are thousands of others that could be discussed in a similar manner.
There is no doubt that U.S. manufacturers are being challenged by companies in Mexico, China, India, Brazil, Indonesia, and all over the world—but that is nothing new. The question is whether or not the United States can respond effectively to such challenges today as it has done in the past. Don’t forget that much, if not most, of the machinery and equipment being used in foreign plants, was produced in the United States. Note, too, that many companies—like Honda and Toyota—have built manufacturing plants in the United States.
This video features Ball metal beverage containers. You’ve seen them everywhere. But have you given any thought to how those cans came to be? Have you wondered why Ball has been so successful in the United States that it expanded operations by buying four U.S. manufacturing plants from brewer Anheuser-Busch InBev?
The text mentions several things that U.S. manufacturers are doing to stay competitive in today’s global markets. They include focusing on customers; maintaining close relationships with suppliers (e.g. using just-in-time inventory control); practicing continuous improvement; focusing on quality; saving on costs through site selection; utilizing the Internet, and adopting new production processes like computer-integrated manufacturing. Foreign businesses are busy copying what we do, so U.S. producers need to do things better and faster and cheaper if they can. Speaking of cans, you can see and hear what Ball is doing to stay competitive in the video. Note that Ball is using a continuous process. What other processes might the company use?
U.S. companies are using computer-aided design and computer-aided manufacturing, united in computer-integrated manufacturing. They also do flexible manufacturing, which means they can produce a variety of products using the same machinery. It should not surprise you to learn that Ball located its facilities close to its customers. That makes distribution faster, easier and cheaper.
Of course, quality is a key consideration in any manufacturing plant. Can you imagine trying to open a can and having the opener break off in your fingers or having a can that leaks all over your car? Manufacturers try for zero defects but often settle for some slightly lower standard such as Six Sigma (only 3.4 defects per million).
Next time you take a cold drink from a can, think about Ball and the other companies that make the United States a major producer of consumer goods. Think, too, of the opportunities that will present themselves to tomorrow’s college graduates. Students seem less attracted to manufacturing today, but that means more opportunities tomorrow for those students who see growth in some areas of manufacturing. That includes, of course, companies that produce solar panels, power plants, and more. You only have to look around your home or office to see the many products being made and the many products that will be made using biotechnology, nanotechnology, and so on.
1. What is the situation of manufacturers in your area/state? Are they hiring or firing more?
2. What factors affect corporation's decisions to offshore manufacturing to other countries? Do you think this is good for an economy? Why or Why Not?
3. Do you think an economic system can exist without manufacturing of goods? Explain.
In: Operations Management
3a. Time magazine conducted a telephone poll and asked the question "Should the federal tax on cigarettes be raised to pay for health care reform?" Of the 605 non-smokers polled in 351 said yes and 101 of the 195 smokers said yes. Is there enough evidence to state there is a difference between the proportion of smokers and non-smokers who believe the federal tax on cigarettes should be raised to pay for health care reform?
b. You share your results with your friend who has not taken statistics. Your friend says, "it's obvious that a lower percentage of smokers believe the tax should be raised. Why are you saying they are the same?" Answer your friend so he/she will understand the conclusion you made in part a.
In: Statistics and Probability
1. A survey of magazine subscribers showed that 45.8% rented a car during the past 12 months for business reasons, 54% rented a car during the past 12 months for personal reasons, and 30% rented a car during the past 12 month for both business and personal reasons.
(a) (3 points) What is the probability that a subscriber rented a car during the past 12 months for business or personal reasons?
(b) (1 points) What is the probability that a subscriber did not rent a car during the past 12 months for either business or personal reasons?
In: Statistics and Probability
A consumer product magazine recently ran a story concerning the increasing prices of digital cameras. The story stated that digital camera prices dipped a couple of years ago, but now are beginning to increase in price because of added features. According to the story, the average price of all digital cameras a couple of years ago was $215.00. A random sample of n = 200 cameras was recently taken and entered into a spreadsheet. It was desired to test to determine if that average price of all digital cameras is now more than $215.00. Find the large-sample rejection region appropriate for this test if we are using .
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Reject H0 if z < -1.645 or z > 1.645. |
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Reject H0 if z < -1.96 or z > 1.96. |
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Reject H0 if z > 1.645. |
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Reject H0 if z < -1.96. |
In: Statistics and Probability
For a new study conducted by a fitness magazine,
240
females were randomly selected. For each, the mean daily calorie consumption was calculated for a September-February period. A second sample of
210
females was chosen independently of the first. For each of them, the mean daily calorie consumption was calculated for a March-August period. During the September-February period, participants consumed a mean of
2385.5
calories daily with a standard deviation of
222
. During the March-August period, participants consumed a mean of
2414.5
calories daily with a standard deviation of
252.5
. The population standard deviations of daily calories consumed for females in the two periods can be estimated using the sample standard deviations, as the samples that were used to compute them were quite large. Construct a
90%
confidence interval for
−μ1μ2
, the difference between the mean daily calorie consumption
μ1
of females in September-February and the mean daily calorie consumption
μ2
of females in March-August. Then complete the table below
| What is the lower limit of the 90% confidence interval? | |
| What is the upper limit of the 90% confidence interval? |
In: Math