
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Question
Adam Marty recently joined North Valley Real Estate and was assigned twenty homes to market and show. When he was hired, North Valley assured him that the twenty homes would be fairly assigned to him. When he reviewed the selling prices of hisassigned homes, he thought that the prices were much below the average of $357,000. Adam was able to find the data of how the other agents in the firm were assigned to the homes. Use statistical inference to analyze the “fairness” that homes

Transcribed Image Text:Aucune
SIM
5:31 PM
@ 17 %
The North Valley Real Estate
record Agent
Price
Size
Bedrooms Baths Pool (yes is 1)
Garage (Yes is 1) Days
Township Mortgage type
Years FICO Default (Yes is 1)
1 Marty
206424
1820
1,5
2 Fixed
1
33
2 824
2 Rose
346150 3010
3
2
36
4 Fixed
9 820
3 Carter
372360 3210
4
3
1
21
2 Fixed
18 819
4 Peterson
310622
3330
3
2,5
1
26
3 Fixed
17 817
5 Carter
496100
4510
6
4,5
1
13
4 Fixed
17
816
6 Peterson
294086 3440
4
3
1
1
31
4 Fixed
19
813
7 Carter
228810 2630
4
2,5
1
39
4 Adjustable
10
813
8 Isaacs
9 Peterson
384420 4470
3,5
26
2 Fixed
6 812
416120
4040
5
3,5
1
26
4 Fixed
810
10 Isaacs
487494
4380
4
1
1
32
3 Fixed
6 808
11 Rose
448800 5280
6.
4
35
4 Fixed
8 806
1
9 805
9 801
12 Peterson
388960
4420
4
3
1
50
2 Adjustable
1
13 Marty
335610 2970
3
2.5
1
25
3 Adjustable
1
14 Rose
276000 2300
1,5
34
1 Fixed
20
798
15 Rose
346421 297o
4
1
1
17
3 Adjustable
10 795
16 Isaacs
453913
3660
6.
4
1
1
12
3 Fixed
18 792
17 Carter
376146 3290
5
3,5
1
1
28
2 Adjustable
9 792
1
18 Peterson
694430
5900
3,5
1
1
36
3 Adjustable
10 788
19 Rose
251269 2050
3
2
1
1
38
3 Fixed
16 786
20 Rose
547596 4920
6.
4,5
1
1
37
5 Fixed
2 785
21 Marty
214910 1950
1,5
1
20
4 Fixed
784
22 Rose
188799
1950
2
1,5
1
52
1 Fixed
10 782
23 Carter
459950 4680
4
3
1
1
31
4 Fixed
8 781
1 Fixed
1 Fixed
5 Adjustable
24 Isaacs
264160 2540
3
2,5
1
40
18 780
25 Carter
393557
3180
4
3
1
1
54
20
776
26 Isaacs
478675
4660
3,5
1
1
26
9 773
27 Carter
384020 4220
3,5
1
23
4 Adjustable
9 772
1
28 Marty
313200
3600
4
3
1
31
3 Fixed
19 772
29 Isaacs
274482
2990
3
1
37
3 Fixed
5
769
30 Marty
167962 1920
2.
1,5
1
1
31
5 Fixed
6 769
31 Isaacs
175823
1970
2.
1,5
1
28
5 Adjustable
9 766
1
32 Isaacs
226498
2520
4
3
1
1
28
3 Fixed
8 763
1
33 Carter
316827
3150
4
3
1
1
22
4 Fixed
2 759
1
34 Carter
189984 1550
2.
1,5
1
22
2 Fixed
17 758
35 Marty
366350
3090
3
2
1
1
23
3 Fixed
5 754
1
36 Isaacs
416160 4080
4
3
1
25
4 Fixed
12
753
37 Isaacs
308000
3500
4
1
37
2 Fixed
18
752
38 Rose
294357
2620
3
1
1
15
4 Fixed
10
751
39 Carter
337144 2790
4
3
1
1
19
3 Fixed
15 749
40 Peterson
299730 2910
3
31
2 Fixed
13
748
5 746
9 741
41 Rose
445740 4370
4
3
1
19
3 Fixed
1 Adjustable
5 Fixed
5 Adjustable
42 Rose
410592 4200
1
1
27
1
43 Peterson
667732 5570
3,5
1
1
29
4 740
44 Rose
523584 5050
6.
4
1
1
19
10 739
45 Marty
336000
3360
3
32
3 Fixed
6 737
46 Marty
202598
2270
3
1
28
1 Fixed
10 737
47 Marty
326695 2830
2,5
1
30
4 Fixed
8 736
48 Rose
321320 2770
3
1
23
4 Fixed
6 736
49 Isaacs
246820 2870
4
3
1
27
5 Fixed
13
735
546084 5910
5 Adjustable
10 731
50 Isaacs
6.
1
1
35
51 Isaacs
793084
174528
6800
5.5
1
1
27
4 Fixed
6 729
52 Isaacs
1600
1,5
1
39
2 Fixed
15 728
53 Peterson
392554
3970
4
3
1
1
30
4 Fixed
17 726
54 Peterson
263160
3060
3.
1
26
3 Fixed
10 726
55 Rose
237120
1900
1,5
1
14
3 Fixed
18 723
15 715
5 710
56 Carter
225750 2150
2
1,5
1
1
27
2 Fixed
1 Fixed
5 Fixed
57 Isaacs
848420
7190
6.
4
1
49
58 Carter
371956 3110o
3,5
1
29
8 710
59 Carter
404538
3290
3.5
1
1
24
2 Fixed
14 707
60 Rose
250090
2810
4
1
18
5 Fixed
11
704
61 Peterson
369978
3830
4
2.5
1
1
27
4 Fixed
10
703
62 Peterson
209292 1630
2.
1,5
1
18
3 Fixed
10 701
63 Isaacs
190032
1850
1.5
1
1
30
4 Adjustable
2 675
64 Isaacs
216720
2520
3
2,5
2
4 Adjustable
5
674
1
65 Marty
323417 3220
4
1
4 Adjustable
1 Adjustable
1 Adjustable
3
22
2 673
66 Isaacs
316210 3070
3
30
1 673
67 Peterson
226054 2090
1,5
1
1
28
6 670
68 Marty
183920 2090
3
30
2 Adjustable
8.
669
1
69 Rose
248400 2300
3
2,5
1
1
50
2 Adjustable
4 667
70 Isaacs
466560 5760
5
3,5
42
4 Adjustable
3 665
71 Rose
8 662
2 656
667212 6110
3 Adjustable
1 Adjustable
5 Adjustable
3 Adjustable
6
1
1
21
1
72 Peterson
362710 4370o
4
2,5
1
24
73 Rose
265440 3160
3,5
1
1
22
3 653
7 652
7 647
74 Rose
706596 6600
7
5
1
1
40
1
75 Marty
293700 3300
14
4 Adjustable
1
76 Marty
199448 2330
1,5
1
1
25
3 Adjustable
5 644
1
2 Adjustable
2 Adjustable
1 Adjustable
4 Adjustable
77 Carter
369533
4230
4
3
1
1
32
2 642
78 Marty
79 Marty
230121
2030
2.
1,5
1
21
3 639
169000
1690
1,5
20
7 639
1
80 Peterson
190291
2040
2
1,5
1
1
31
6.
631
1
81 Rose
393584
4660
4
3
1
1
34
3 Adjustable
7 630
1
82 Marty
363792 2860
3
2,5
1
48
5 Adjustable
3
626
2 Adjustable
1 Adjustable
83 Carter
360960 3840
6.
4,5
32
5
626
1
84 Carter
310877
3180
3
2
1
1
40
6.
624
1
85 Peterson
919480
7670
8
5.5
1
1
30
4 Adjustable
1 623
86 Carter
392904 3400
2
1
40
2 Adjustable
8 618
1
4 Adjustable
1 Adjustable
1 Adjustable
87 Carter
200928
1840
2
1,5
1
1
36
3
618
1
88 Carter
537900
4890
6.
4
1
23
7 614
89 Rose
258120 2390
3
2.5
1
23
6 614
1
90 Carter
558342 6160
6.
1
1
24
3 Adjustable
7 613
91 Marty
3 Adjustable
5 Adjustable
302720 3440
4
2,5
1
38
3 609
1
92 Isaacs
240115 2220
1,5
1
39
609
93 Carter
793656 6530
5
1
1
53
4 Adjustable
3 605
1

Transcribed Image Text:Aucune SIM
5:31 PM
@ 17 %
The North Valley Real Estate
16 Isaacs
453913 3660
6
4
1
12
3 Fixed
18 792
17 Carter
376146 3290
3,5
1
1
28
2 Adjustable
792
1
18 Peterson
694430 5900
3,5
1
1
36
3 Adjustable
10 788
19 Rose
251269 2050
3
2
1
1
38
3 Fixed
16 786
20 Rose
547596
4920
6.
4,5
1
1
37
5 Fixed
2 785
21 Marty
214910 1950
1,5
1
20
4 Fixed
6 784
22 Rose
188799 1950
1,5
1
52
1 Fixed
10 782
23 Carter
459950 4680
4
3
1
1
31
4 Fixed
781
1 Fixed
1 Fixed
5 Adjustable
4 Adjustable
24 Isaacs
264160 2540
3.
2,5
1
40
18 780
25 Carter
393557 3180
4
3
1
54
20 776
26 Isaacs
478675
4660
5
3,5
1
26
9 773
27 Carter
384020
4220
5
3,5
1
23
772
1
28 Marty
313200
3600
4
3
1
31
3 Fixed
19 772
29 Isaacs
274482 2990
3 Fixed
5 769
30 Marty
167962
1920
2
1,5
1
1
31
5 Fixed
6.
769
175823
1970
1,5
5 Adjustable
9 766
31 Isaacs
2
1
28
1
32 Isaacs
226498 252o
4
3
1
1
28
3 Fixed
8 763
1
33 Carter
316827
3150
4
3
1
1
22
4 Fixed
2 759
1
34 Carter
189984
1550
1.5
1
22
2 Fixed
17 758
35 Marty
366350
3090
3.
23
3 Fixed
5 754
2
1
1
1
36 Isaacs
416160
4080
4
3
1
25
4 Fixed
12 753
37 Isaacs
308000 3500
4
3
1
37
2 Fixed
18
752
38 Rose
294357
2620
4
3
1
1
15
4 Fixed
10 751
337144 2790
4
19
3 Fixed
15 749
39 Carter
1
1
40 Peterson
299730 2910o
31
2 Fixed
13 748
5 746
9 741
41 Rose
445740 4370
4
3
1
19
3 Fixed
1 Adjustable
5 Fixed
5 Adjustable
42 Rose
410592
4200
3
1
1
27
1
43 Peterson
667732 5570
5
3,5
1
1
29
4 740
44 Rose
523584 5050
6.
4
1
1
19
10 739
45 Marty
336000 3360
3
2
32
3 Fixed
737
46 Marty
202598 2270
3
1
28
1 Fixed
10 737
47 Marty
326695 2830
3
2,5
1
30
4 Fixed
8 736
48 Rose
321320 2770
3
2
1
23
4 Fixed
6 736
49 Isaacs
246820 287o
4
3
1
27
5 Fixed
13 735
50 Isaacs
546084
5910
4
35
5 Adjustable
10 731
6.
1
1
51 Isaacs
793084 6800
5,5
1
1
27
4 Fixed
6 729
52 Isaacs
174528 1600
2.
1,5
1
39
2 Fixed
15 728
53 Peterson
392554 3970
4.
3
1
1
30
4 Fixed
17 726
54 Peterson
263160
3060
3
1
26
3 Fixed
10 726
55 Rose
237120
1900
2
1,5
1
14
3 Fixed
18
723
56 Carter
225750 2150
2.
1,5
1
27
2 Fixed
15 715
1 Fixed
5 Fixed
57 Isaacs
848420
7190
6.
4
49
5 710
58 Carter
371956
3110
3,5
1
1
29
710
59 Carter
404538
3290
3,5
1
1
24
2 Fixed
14
707
60 Rose
250090 2810
4
3
1
18
5 Fixed
11
704
61 Peterson
369978 3830
4
2,5
1
1
27
4 Fixed
10 703
62 Peterson
209292
1630
2
1,5
1
18
3 Fixed
10
701
63 Isaacs
190032 1850
1.5
1
1
30
4 Adjustable
2 675
64 Isaacs
216720 2520
3
2,5
2
4 Adjustable
5 674
1
65 Marty
323417
3220
4 Adjustable
1 Adjustable
1 Adjustable
4
1
1
22
2
673
66 Isaacs
316210 3070
3
2
30
1
673
67 Peterson
226054 2090
1,5
1
1
28
6 670
68 Marty
183920
2090
3
30
2 Adjustable
8 669
1
69 Rose
248400 2300
3.
2,5
1
1
50
2 Adjustable
4 667
70 Isaacs
466560 5760
3,5
1
42
4 Adjustable
3
665
667212 6110
6.
4
21
8 662
3 Adjustable
1 Adjustable
5 Adjustable
3 Adjustable
71 Rose
1
1
1
72 Peterson
362710 4370
4
2,5
1
24
2 656
73 Rose
265440 3160
5
3,5
1
1
22
3
653
74 Rose
706596 6600
7
5
1
1
40
7 652
1
75 Marty
293700 3300
3
2
14
4 Adjustable
7 647
1
76 Marty
3 Adjustable
2 Adjustable
2 Adjustable
1 Adjustable
199448 2330
1,5
1
1
25
5 644
1
77 Carter
369533
4230
4
3
1
1
32
2
642
78 Marty
230121
2030
2
1,5
1
21
3
639
79 Marty
169000
1690
2
1,5
20
7 639
1
80 Peterson
81 Rose
190291
2040
2.
1,5
1
1
31
4 Adjustable
6 631
1
393584
4660
4
3
1
1
34
3 Adjustable
7 630
1
82 Marty
363792 2860
3
2,5
1
1
48
5 Adjustable
3 626
83 Carter
360960
3840
6.
4,5
1
32
2 Adjustable
5 626
1
84 Carter
310877 3180
2
1
40
1 Adjustable
6 624
1
85 Peterson
919480 7670
8.
5,5
1
1
30
4 Adjustable
1
623
86 Carter
392904
3400
3
1
40
2 Adjustable
618
1
3 618
4 Adjustable
1 Adjustable
1 Adjustable
87 Carter
200928 1840
1.5
1
1
36
1
88 Carter
537900 4890
6.
4
1
23
7 614
89 Rose
258120 2390
3.
2,5
1
23
6.
614
1
90 Carter
558342 6160
6.
4
1
1
24
3 Adjustable
7
613
91 Marty
302720 3440
4
2.5
1
38
3 Adjustable
3 609
1
92 Isaacs
240115
2220
1,5
1
39
5 Adjustable
609
93 Carter
793656 6530
7
5
1
1
53
4 Adjustable
605
1
94 Peterson
218862 1930
1,5
1
58
4 Adjustable
1 604
95 Peterson
383081
3510
3
2
1
1
27
2 Adjustable
6 601
1
96 Marty
351520 3380
3
1
35
2 Adjustable
599
1
97 Peterson
841491 7030
6
4
1
1
50
4 Adjustable
596
1
98 Marty
336300 2850
1 Adjustable
6 595
3
2,5
28
1
99 Isaacs
312863
3750
6.
4
1
12
4 Adjustable
2 595
100 Carter
275033
3060
1
1
27
3 Adjustable
3 593
229990 2110
3 Adjustable
5 Adjustable
101 Peterson
1,5
37
6 591
1
102 Isaacs
195257 2130
1.5
1
11
8
591
1
103 Marty
194238
1,5
30
7 590
2 Adjustable
5 Adjustable
5 Adjustable
1650
2.
1
1
1
104 Peterson
348528
2740
3
1
1
27
3
584
1
105 Peterson
241920 2240
2
1.5
1
34
583
1
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- Samantha took an exam in her statistics class and received 90 out of 100. Samantha thought that was a good score, but she wanted to know how high her score was in relation to the rest of the class. Her professor said her Z-score was -0.29. How should Samantha interpret her Z-score? a. Samantha’s score is 0.29 points above the class mean.b. Samantha’s score is 29% above than the class mean.c. Samantha’s score is 0.29 standard deviations above the class mean.d. Samantha’s score is 0.29 standard deviations below the class mean.arrow_forwardA statistics teacher asked two different students, Lexie and Jennifer, to go to Wegmans and sample 30 shoppers each. The population of interest for both people can be defined as, “People who shop at the Johnson City, NY Wegmans store”. Here is what each person did to collect their sample: Lexie: She stood outside at the entrance to the store on 3 different days and times and surveyed every 15th person to walk by her. She surveyed 10 people each time to get her 30. Jennifer: She went to Wegmans after her nursing shift first thing Wednesday morning to buy deodorant since she ran out. When she was in the pharmacy area she surveyed all the people around her and then, to get up to 30 surveys, she went to the health food section and surveyed everyone she was there. Identify at least 2 specific reasons why Lexie’s approach is more likely to give a representative sample. Consider sources of bias, or types of shoppers who might be excluded by Jennifer’s approach.…arrow_forwardElaine is interested in determining if men are more satisfied in their jobs than women in the healthcare industry. She administers a job satisfaction questionnaire to 20 men and 20 women working in hospital administration. Her grouping variable is gender and dependent variable is job satisfaction. The job satisfaction scale consists of 8 items measured using a 5-point rating scale. A higher score on this scale would indicate high job satisfaction. The maximum score that can be obtained on the scale is 40. We can assume that job satisfaction scores are normally distributed. Use the appropriate T test with a significance level of 0.05 to test the hypothesis. Research Question Do the mean job satisfaction scores differ for men and women working in the hospital administration department? Hypothesis The mean job satisfaction scores do not differ for men and women working in the hospital administration department. Compute an independent sample t test on these data. Report…arrow_forward
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