Question

January	February
902.79	640.77
7208.82	4571.22
4240.01	2271.57
79.89	299.69
4038.81	1376.69
89.24	−120.78
3290.41	1928.63
2418.77	2609.13
83.87	144.74
6.42	393.11
0.00	40.41
564.15	295.64
2714.19	850.07
187.25	162.07
3266.22	2411.62
1525.08	957.05
1358.98	38.013
733.71	2656.94
75.12	64.94
70.27	−70.21
633.98	1860.28
1040.93	478.78
554.05	995.75
1016.82	774.36
1304.09	3364.08
249.63	5.53
48.71	96.94
871.96	890.94
485.52	485.28
616.84	1486.08
1572.31	890.16
422.54	392.15
769.75	323.26
56.55	0.00
1486.28	2253.16
495.57	389.88
1064.46	1065.19
510.06	131.43
5646.18	4950.25
5.51	5.49
871.18	591.22
1636.08	3364.92
92.19	86.03
669.73	1365.59
828.78	280.79
69.28	67.97
830.59	1056.46
2299.82	3314.49
270.26	14.12
210.28	160.52
1011.69	518.88
1043.91	2021.14
298.63	635.58
−30.02	0.00
1635.37	393.02
1731.19	1322.69
0.00	65.08
31.41	28.74
4.95	77.24
1088.07	891.82
26.85	29.01
120.23	32.24
2006.84	816.26
291.36	780.06
103.98	0.00
53.02	66.23
2842.67	1532.77
675.79	293.71
221.51	171.75
37.77	4.78
533.74	881.16
1931.68	1063.71
692.66	914.03
6803.75	5939.59
392.94	466.18
1308.42	303.27
797.16	496.92
0.00	266.64
1040.68	59.41
564.86	206.63
339.26	411.67
5280.75	5318.55
40.09	72.65
43.37	38.42
653.13	480.28
1071.88	416.25
2333.95	1788.08
91.53	175.37
1434.26	1109.71
719.47	307.51
28.58	24.15
980.13	1216.73
1577.48	1810.77
0.00	468.16
161.85	147.59
493.52	1996.78
533.68	934.53
462.22	114.55
1477.72	2093.12

Financial analysts know that January credit card charges will generally be much lower than those of the month before. What about the difference between January and the next month? Does the rend continue? The accompany ng data set contains e mon credit card charges of a random sam 。99 car holders. Complete a a) through e) below. EB Click the icon to view the monthly credit card charges a) Build a regression model to predict February charges from January charges FebJan (Round to two decimal places as needed.) Check the conditions for this model. Select all of the true statements related to checking the conditions □ A. All of the conditions are definitely satisfied. B. The Nearly Normal Condition is not satisfied □ C. The Equal Spread Condition is not satisfied. D. The Linearity Condition is not satisfied. E. The Randomization Condition is not satisfied. b) How much, on average, will cardholders who charged $2000 in January charge in February? Round to the nearest cent as needed.) c) Give a 95% confidence interval for the average February charges of cardholders who charged $2000 in January. 毛 c) Give a 95% confidence interval for the average February charges of cardholders who charged $2000 in January. (Round to the nearest cent as needed.) d) From part c), give a 95% confidence interval for the average decrease in the charges of cardholders who charged $2000 in January. (Round to the nearest cent as needed.) e) What reservations, if any, would a researcher have about the confidence intervals made in parts c) and d)? Select all that apply. A. The data are not independent, so the confidence intervals are not valid. B. The residuals show increasing spread, so the confidence intervals may not be valid. □ C. The data are not linear, so the confidence intervals are not valid. D. The residuals show a curvilinear pattern, so the confidence intervals may not be valid E. Aresearcher would not have any reservations. The confidence intervals are valid.

Answer 1

a)

Residual Plots for January Normal Probability Plot Versus Fits 4000 2000 50 2000 01 -2000 2000 1500 3000 4500 6000 Residual Fitted Value Versus Order Histogram 401 4000 30 2000 2 20 10 2000 2000 1000 1000 2000 3000 4000 Residual 1 10 20 30 40 50 60 70 90 Observation Order

dud e E. 1冉-2000 ISI 그 .GS

| D)GrVD a 95% oontdence mervai tor tho averagn January charges or cardholdns whochanged $2000 n Docembar. 4 Round o he neareet cert as needed) Excel fiumu -couNTBS:B 105 1543.471 9n.rs df-n-2- 1,336A Mean: xbar)- 202.6979 2,000 -FORECAST E11,C8 C105 B8 B106) 4141.82 873.21Ro.25 874.39 SIENCsci06BS B106) Syx- 1932.92 2418.49 vsQB8 B100) 9917 3.92 242215256.96 503.9 9347 10 682.55 564.45 Conidesce 95% 2161.01 2712.73 t-ait- 198 Lower Limit of C.I- 0.1 1124.9 E12-E20 18 2507.68 3262.37 Upper Limit of CI 1,709.1 3+F43 B39

ontamn С.mm

Confidence Interval Estimate Data X Value 2000 Confidence Level 95% Intermediate Calculations Sample Size Degrees of Freedom 97 t Value 1.984723 XBar, Sample Mean of X 1335.816 Sum of Squared Differences from XBar 2.42E+08 Standard Error of the Estimate 873.8713 h Statistic 0.011922 1519.961 For Average Y Interval Half Width 189.3766 Confidence Interval Lower Limit1330.5840 Confidence Interval Upper Limit 1709.337 For Individual Response Y 1744.7010 Interval Half Width Prediction Interval Lower Limit 224.7404 Prediction Interval Upper Limit 3264.662

Can c1c.com. 132G6G deCsease Ala Py