7. A researcher would like to determine whether any particular age group has a greater risk of influenza-related death. A sample of 50 cases is categorized according to victim’s age. The observed frequencies are as follows:- Number of flu-related deaths Under 30 30 – 60 Over 60 5 5 40 Note that in the city from which the sample was selected, 30% of the population is in the “under 30” bracket, 40% is in “30 -60”, and 30% is in “over 60”. Can the researcher conclude that risk differs with age? Test at α = .05
7. A researcher would like to determine whether any particular age group has a greater risk of influenza-related death. A sample of 50 cases is categorized according to victim’s age. The observed frequencies are as follows:- Number of flu-related deaths Under 30 30 – 60 Over 60 5 5 40 Note that in the city from which the sample was selected, 30% of the population is in the “under 30” bracket, 40% is in “30 -60”, and 30% is in “over 60”. Can the researcher conclude that risk differs with age? Test at α = .05
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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7. A researcher would like to determine whether any particular age group has a greater risk of influenza-related death. A sample of 50 cases is categorized according to victim’s age. The observed frequencies are as follows:-
Number of flu-related deaths |
||
Under 30 |
30 – 60 |
Over 60 |
5 |
5 |
40 |
Note that in the city from which the sample was selected, 30% of the population is in the “under 30” bracket, 40% is in “30 -60”, and 30% is in “over 60”. Can the researcher conclude that risk differs with age? Test at α = .05

Transcribed Image Text:BHPY2044 STATISTICAL TECHNIQUES FOR PSYCHOLOGY II
The Chi-Square Distribution*
*The table entries are critical values of x.
Critical
Proportion in Critical Region
0.025
df
0.10
0.05
0.01
0.005
5.02
7.38
6.63
7.88
2.71
4.61
3.84
9.21
10.60
5.99
7.81
2
3
6.25
9.35
I 1.34
12.84
7.78
11.14
13.28
14.86
9.49
11.07
4
5
9.24
12.83
15.09
16,75
14.45
16.81
18.55
10.64
12.02
13.36
12.59
14.07
15.51
7
16.01
18.48
20.28
17.53
20.09
21.96
19.02
21.67
23.59
16.92
18.31
9
14.68
10
15.99
20.48
23.21
25.19
26.76
28.30
29.82
19.68
21.92
24.72
17.28
18.55
19.81
21.06
11
12
21.03
23.34
26.22
24.74
27.69
22.36
23.68
13
14
26.12
29.14
31.32
30.58
32.00
32.80
25.00
26.30
27.49
28.85
15
22.31
16
23.54
34.27
17
24.77
27.59
30.19
33.41
35.72
37.16
38.58
18
25.99
28.87
31.53
34.81
36.19
30.14
31.41
19
27.20
32.85
20
28.41
34.17
37.57
40.00
38.93
40.29
41.40
32.67
33.92
35.17
36.42
37.65
38.89
40,11
41.34
42.56
43.77
35.48
36.78
38.08
39.36
40.65
41.92
43.19
21
29.62
30.81
32.01
42.80
44.18
22
41.64,
42.98
44.31
23
33.20
34.38
35.56
36.74
37.92
39.09
45.56
46.93
48.29
49.64
24
25
26
27
45.64
46.96
48.28
50.99
52.34
53.67
28
44.46
49.59
50.89
29
45.72
30
40.26
46.98
63.69
66.77
59.34
71.42
83.30
95.02
106.63
40
50
51.81
63.17
74.40
85.53
96.58
107.56
118.50
55.76
67.50
76.15
79.49
88.38
100.42
91.95
79.08
90.53
60
70
104.22
112.33
116.32
101.88
113.14
124.34
80
124.12
135.81
118.14
128.30
90
100
129.56
140.17
Table 8 of E. Pearson and H. O. Hartley, Bioinetrika Tables for Statisticians, 3rd ed. New York:
Cambridge University Press, 1966. Adapted and reprinted with permission of the Biometrika
trustees.
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