Business Analytics

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Question description

Question 1 A group of investors wants to develop a chain of fast-food restaurants. In determining potential costs for each facility, they must consider, among other expenses, the average monthly electric bill. They decide to sample some fast-food restaurants currently operating to estimate the monthly cost of electricity. They want to be 90% confident of their results and want the error of the interval estimate to be no more than $100. They estimate that such bills range from $600 to $2,500. How large a sample should they take? Question 2 Suppose a study reports that the average price for a gallon of self-serve regular unleaded gasoline is $3.16. You believe that the figure is higher in your area of the country. You decide to test this claim for your part of the United States by randomly calling gasoline stations. Your random survey of 25 stations produces the following prices (all in $). Assume gasoline prices for a region are normally distributed. Do the data you obtained provide enough evidence to reject the claim? Use a 1% level of significance. 3.27 3.29 3.16 3.20 3.37 3.20 3.23 3.19 3.20 3.24 3.16 3.07 3.27 3.09 3.35 3.15 3.23 3.14 3.05 3.35 3.21 3.14 3.14 3.07 3.10 Question 3 Where do CFOs get their money news? According to Robert Half International, 47% get their money news from newspapers, 15% get it from communication/colleagues, 12% get it from television, 11% from the Internet, 9% from magazines, 5% from radio, and 1% do not know. Suppose a researcher wants to test these results. She randomly samples 67 CFOs and finds that 40 of them get their money news from newspapers. Does the test show enough evidence to reject the findings of Robert Half International? Use a = .05. Unit 3 [GB513: Business Analytics] Question 4 To answer this question, use the Data Analysis Toolpack in Excel and select “t-Test: Two-Sample Assuming Equal Variances” from the list of available tools. Explain your answer (how did you decide if men spend more) and include the output table. Some studies have shown that in the United States, men spend more than women buying gifts and cards on Valentine’s Day. Suppose a researcher wants to test this hypothesis by randomly sampling nine men and 10 women with comparable demographic characteristics from various large cities across the United States to be in a study. Each study participant is asked to keep a log beginning one month before Valentine’s Day and record all purchases made for Valentine’s Day during that one-month period. The resulting data are shown below. Use these data and a 1% level of significance to test to determine if, on average, men actually do spend significantly more than women on Valentine’s Day. Assume that such spending is normally distributed in the population and that the population variances are equal. Men Women 107.48 125.98 143.61 45.53 90.19 56.35 125.53 80.62 70.79 46.37 83.00 44.34 129.63 75.21 154.22 68.48 93.80 85.84 126.11

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