Question.2957 - I. Find the sales data for Apple here: http://images.apple.com/pr/pdf/q1fy13datasum.pdf. (30 points) a. How would you estimate the average revenues for Q1’13 using operating segments? Which is the best method? How would you interpret an average across countries here? b. Is there enough information to estimate the average using the method you recommend? c. In product summary why it is important to have the units listed? If you want to estimate average revenue for Apple products do you need to use the units? How? II. Review the data in Table 1. It covers the median income for the top 25 Georgia counties. (50 points) a. If John earns $62,591 annually in Henry County what would change for him if he moves to Cherokee county? b. You want to demonstrate this data, how would you categorize it? c. If you want to show the number of counties with a median income within a certain range how do you identify those ranges? How many bins you will choose? What kind of representation you will choose? d. Use Excel to draw the graph and submit it as part of your work. e. Consider the Median Income as a variable, report Mean, Median, STD, Variance and Quartiles for it. f. Would you identify the counties which are between 25 percentile and 75 percentile (second and third quartiles)? Table 1 Rank County Media n 1 Forsyth $84,56 7 2 Fayette $77,49 1 3 Oconee $74,63 0 4 Columbia $68,98 6 5 Cherokee $66,97 2 6 Henry $63,89 2 7 Paulding $63,66 3 8 Harris $63,35 1 9 Cobb $62,89 3 10 Coweta $59,84 8 11 Gwinnett $58,73 2 12 Bryan $58,09 2 13 Lee $57,04 4 14 Fulton $56,31 3 15 Pike $55,67 4 16 Effingha m $54,67 8 17 Monroe $53,80 5 18 Dawson $53,21 5 19 Rockdale $51,26 5 20 Douglas $50,79 8 21 Pickens $50,79 0 22 Houston $50,73 3 23 Jackson $50,59 1 24 Walton $50,32 1 25 Newton $50,13 7 26 DeKalb $50,09 2 III. Display the data in Table 1 using Stem Leaf approach and dot plot. (20 points)
Answer Below:
1 a) The average revenues for Q1’13 using operating segments can be estimated by dividing the total revenue with number of operating segments. The best method would be finding weighted average where each operating segment is assigned a weight based on one or more parameters. For example, the weight can be assigned on the basis of cost of products supplied. Each operating segment is given a weight equivalent to the ratio of the cost of products supplied to it by total cost of products supplied. Also the average can be calculated in a more suitable manner by units of different products supplied to different operating segments. Average across countries is estimated by first dividing the operating segments into different countries from which Apple generates its revenue. Then simple arithmetic mean can be calculated by dividing total revenue from total number of countries from which the revenues are generated. b) No there is not enough information to estimate the average using the method you recommend. We do not know how many units of each product are supplied to each Operating Segment. So we cannot estimate the exact revenue by that product in a particular Operating Segment. c) In product summary it is important to have the units listed because by this we can have an estimate of which product is generating more revenue for Apple. By listing the units, we can set appropriate weights to each operating segment and a better average can be estimated based on it. For estimating the average revenue for Apple products, I would need the units because average revenue for each product will be revenue generated by that product divided by the number of units of that product. For example iPhone generated a revenue of $30,660 in Q1’13 and total units of iPhone were 47,789. So the average revenue generated by iPhone is 30,660/47,789 = $0.64/unit. 2 a) Rank and he will fall lower in the income table. b)we would categorise the data based on range of median income.we will form various bin and shall use the excel tool to find the number of datas in respective bin c) We find all of the data between 50000 to 90000. I would like to take bin of 5000 and shall place my data in bins of 50000-55000, 55000-60000 and so on. bin frequenc y 50000 0 55000 11 60000 6 65000 4 70000 2 75000 1 80000 1 85000 1 90000 0 We can see the distribution and graph below. Stem and leaf method will be best in this case. d) 500005500060000650007000075000800008500090000 bin 0 2 4 6 8 10 12 frequency v/s bin e) Mean 59175.88 Median 56678.5 Standard Deviation 9277.425 Sample Variance 8607062 0 Range 34475 1st quartile 50796 median $56,678. 5 3rd quartile 63720.25 f) list of countries between 1 st and third quartile Paulding $63,66 3 Harris $63,35 1 Cobb $62,89 3 Coweta $59,84 8 Gwinnett $58,73 2 Bryan $58,09 2 Lee $57,04 4 Fulton $56,31 3 Pike $55,67 4 Effingha m $54,67 8 Monroe $53,80 5 Dawson $53,21 5 Rockdale $51,26 5 Douglas $50,79 8 3) n 26 mean 59175.8 8 median 56678.5 std. dev. 9277.42 5 minimum 50092 maximu m 84567 Stem-and-Leaf Display Leaf unit: 10000 5 0 0 0 1 1 1 1 1 3 4 5 6 6 7 8 9 6 0 3 3 4 4 7 9 7 5 7 8 5 ********* ******* ******* ** * 50000 60000 70000 80000 90000 Box plot Lower Whiske r Lower Hinge Median Upper Hinge Upper Whiske r 50092 50914.7 5 56678.5 63585 77491 020000400006000080000100000120000More Articles From Statistics
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