ID 70658423 70643581 70546158 70581054 70663771 70412130 70656875 70630419 70569799 70610315 70182357 70656957 70656361 70674824 70639181 70538352 70644836 70645235 70657377 70576192 70616876 70496703 70646484 70576614 70641078 70605488 70398558 70592405 70618234 70604489 70532928 70601003 70558854 70564256 70555910 70663448 70596631 70441659 70497192 70634383 70639118 70659094 Town 1 1 2 1 2 2 1 1 2 1 2 1 2 1 2 2 1 1 1 1 2 1 1 2 2 2 1 1 2 2 2 2 2 2 2 1 1 2 1 1 2 1 Price 399900 425000 489000 509900 599000 599900 699000 759000 799000 815900 990000 995000 1099000 1195000 1198000 1395000 1475000 1495000 1595000 1650000 1675000 1799000 1895000 1990000 1999800 2195000 2495000 2595000 2850000 2950000 2999900 3295000 3395000 3595000 3750000 3785000 4295000 4895000 4950000 5900000 5900000 5999000 Dec-04 1544.23 4300.07 4229.53 202.77 3297.84 873.86 3808.92 1934.24 99.18 504.27 410.91 683.08 2161.15 1123.9 2507.42 1836.68 9.95 2334.25 78.55 101.33 598.33 648.39 235.93 1266.4 2124.12 3.66 306.05 1900.94 559.19 2446.7 2800.47 531.8 536.77 767.63 1958.47 1679.1 2063.8 397.01 5641.7 5.5 2279.68 3817.2 89.17 1451.86 527.61 105.76 1403.9 4231.44 633.28 970.53 348.18 0 50 30 471.7 1116 70.7 31.08 4.95 2522.2 16.96 40.55 259 123 0 109.82 5053.68 3673.89 139.82 76 3153.38 2988.47 651.2 9120.78 916.69 2873.61 797.59 34.55 44.18 478.35 761.86 2350.39 44.27 43.29 1339.48 1127.9 Jan-05 903.46 7211.62 4238.38 79.97 4042.57 89.25 3290.84 2419.34 83.87 6.42 0 564.47 2714.8 187.13 3265.57 1523.77 1359.25 733.57 75.08 70.27 634.12 1041.3 553.56 1017 1304.77 249.48 48.75 872.65 485.45 616.73 1573.77 422.59 770.19 56.57 1486.03 495.66 1064.61 510.28 5642.49 5.5 871.29 1635.18 92.19 669.64 828.87 69.23 830.98 2301.91 270.46 210.49 1011.96 1044.32 298.52 -30 1635.5 1732.43 0 31.4 4.95 1088.26 26.88 120.2 2007.43 291.43 104 53.01 2840.82 675.13 221.66 37.77 533.58 1933.08 692.81 6803.71 393.15 1308.05 796.77 0 1040.29 565.13 339.23 5276.41 40.09 43.37 653.42 1071.4 Feb-05 641.24 4568.16 2269.84 299.89 1377.24 -120.8 1929.67 2609.39 144.84 392.93 40.44 295.68 849.32 162.06 2413.43 956.96 38.03 2655.16 64.92 -70.27 1861.84 478.44 994.95 773.78 3367.35 5.53 96.88 890.67 485.45 1485.26 889.97 391.79 323.38 0 2252.06 389.81 1065.87 131.4 4945.38 5.5 591.81 3363.01 85.98 1366.62 280.77 67.95 1057.52 3316.35 14.13 160.65 519.13 2022.62 635.46 0 393.14 1323.78 65.1 28.77 77.2 892.11 29.01 32.22 816.37 779.52 0 66.29 1531.91 293.72 171.9 4.78 880.93 1062.86 914.77 5942.68 466.19 303.02 497.3 266.42 59.4 206.8 412.05 5322.19 72.63 38.44 480.2 416.64 2800.96 52.13 1294.53 328.42 28.32 598.96 4281.7 567.8 479.65 1615.99 285.65 1284.45 3760.35 2334.72 91.47 1433.73 720.11 28.61 980.38 1576.74 0 161.94 493.95 533.73 462.08 1478.55 1788.96 175.23 1108.77 307.81 24.17 1216.02 1811.39 468.4 147.73 1995.13 935.19 114.56 2092.67 COMM 291 Application of Statistics in Business (fall 2015) ASSIGNMENT 5 Hard Copy Solutions to be Handed In 2:30 pm, Wednesday December 2, 2015 Instructions: This assignment consists of five questions and each question has multiple parts. The spreadsheet titled Asst6_2015_Data.xlsx contains data for questions 1 and 4. Present the parts of your answers in the same order as the questions are asked. Do not include any original data in your printed submission. Use the posted cover page. Grades for assignments without properly completed cover pages will be reduced by one mark. Maintain all precision in your calculations when performing multi-step computations. Round off to fewer decimal places (no more than two) only when you state the final answer. When formatting numbers in Excel, display only as many decimal places as provide decisionmaking value to the reader. Question 1 - Real Estate (5 points) Residents of neighbouring towns have an ongoing disagreement over who lays claim to the higher average price of a single-family home. Since you live in one of these towns, you decide to obtain a random sample of homes listed for sale with a major local realtor to investigate if there's actually difference in the average home price. a) Using the data in the data file (Asst6_2015_Data.xlsx), check the conditions for the test. (1.5 points) b) Write null and alternative hypothesis for the test. (1 point) c) Test the hypothesis and find the P-value. (1.5 points) d) What is your conclusion? (1 point) Question 2 - Regional Internet Usages (5 points) Internet usages rates are available for various countries in the Unites nations Database. Countries were randomly selected from the regions (Africa, Asia, and Europe), and Internet usage (per 100 inhabitants) data from 2005 were retrieved. The data were analyzed to determine if Internet usages were the same across regions. The partially completed analysis of variance (ANOVA) is shown here Source Region Error Total Degrees of Freedom 2 93 95 Sum of Squares 21607 20712 42319 Mean Square F-ratio P-value a) Explain whether this is an observational or experimental study. (.5 point) b) Is this a prospective or retrospective study? Explain. (.5 point) c) State the null and the alternative hypothesis for this test. (1 point) d) Complete the missing values in the table and write down the formulas that you used to compute the missing values. (2 points) e) The P-value of the F-statistic turns out to be 0.002. What can you conclude based on this P-value? Can a causal link between the regions (Africa, Asia, and Europe) and Internet usages be established? Explain your answer. (1 point) Question 3 - Small Business (7 points) The director of a small business development center located in a mid-sized city is reviewing data about its clients. In particular, she's interested in examining if the distribution of business owners across the various stages of business life cycle is the same for white-owned and visible-minority-owned businesses. The data are shown in the table below: Stages in Business Planning Starting Managing Getting Out Business ownership White-owned Visible-minority-owned 11 9 14 11 20 2 15 1 a) Will you test goodness-of-fit or homogeneity (independence)? (.5 point) b) Write the appropriate hypothesis. (.5 point) c) Find the expected counts for each cell and explain why chi-square procedure are not appropriate for this table. (1 point) d) Create a new table by combining categories so that a chi-square procedure can be used. (1 point) e) With this change in the table, what has happened to the degrees of freedom? (.5 point) f) Test the hypothesis about the two groups and state the appropriate conclusion. (3.5 points) Question 4 - Seasonal spending (8 points) Spending on credit cards decreases after the holiday spending season (as measured by amount charged on a credit card in December). The data set in the file (Asst6_2015_Data.xlsx) contains the monthly credit card charges of a random sample of 99 cardholders. a) Check the conditions of a regression model for the dataset. (3.5 point) b) Build a regression model to predict January spending from December's spending. (1 point) c) How much, on average, will cardholders who charged $2000 in December charge in January? (.5 point) d) Give a 95% confidence interval for the average January charges of cardholders who charged $2000 in December? (1.5 points) e) From part d), give a 95% confidence interval for the average decrease in the charges of cardholders who charged $2000 in December? (1 point) f) What reservations, if any, do you have about the confidence intervals you made in part d) and e)? (.5 point)