Chi-Sq - 5.348 + **** + 0.024 + 15.912 + 1.459 + 0.019 + 0.413 + 2.544 + 2.816 + 7.003 + 0.709 + 9.182 + 3.448 + 11.875 + 1.325 + 12.983 - 80.395 DF - *****, P-Value - *w**** No cells with expected counts less than 5. a) Name the random variables present in the table above.

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Chi-Są =
5.348 +
**** +
0.024 + 15.912 +
1.459 +
0.019 +
0.413 +
2.544 +
2.816 +
7.003 +
0.709 +
9.182 +
3.448 + 11.875 +
1.325 + 12.983 = 80.395
DF = *****, P-Value = ******
No cells with expected counts less than 5.
a) Name the random variables present in the table above.
b) Carefully define the null and altermative hypotheses of the Chi Square test
underlying the generation of the above table.
c) Fill in the gaps marked by
** *** ***** *****:
and
本本事車率丰:r-
本 :
d) What is the assumption on which these calculations are based?
e) What is relevance of the statement" No cells with expected counts less than 5."
) Do the records suggest a relationship or independence between age and
department for the employees of this car dealership at the 5% significance level?
Transcribed Image Text:Chi-Są = 5.348 + **** + 0.024 + 15.912 + 1.459 + 0.019 + 0.413 + 2.544 + 2.816 + 7.003 + 0.709 + 9.182 + 3.448 + 11.875 + 1.325 + 12.983 = 80.395 DF = *****, P-Value = ****** No cells with expected counts less than 5. a) Name the random variables present in the table above. b) Carefully define the null and altermative hypotheses of the Chi Square test underlying the generation of the above table. c) Fill in the gaps marked by ** *** ***** *****: and 本本事車率丰:r- 本 : d) What is the assumption on which these calculations are based? e) What is relevance of the statement" No cells with expected counts less than 5." ) Do the records suggest a relationship or independence between age and department for the employees of this car dealership at the 5% significance level?
The human resource manager at a car dealership wants to know if the ages of its employees are
related to the department that they work in. Data was compiled and tabulated in a 2-way
contingency table. The employees were classified according to their age and department.
Expected count3 are printed below observed counts
Saies
Accounts
Markecing Repairs
Total
20-29
10
27
43
88
17.74
26.20
***
23.62
30-39
29
26
38
22
23.18
26.72
34.24
30.86
40-49
33
32
72
82
219
44.15
50.88
65.20
58.77
50-59
81
106
86
54
327
65.92
75.97
97.36
87.75
Total
151
**
223
201
749
Chi-Sq -
5.348 +
**** +
0.024 + 15.912 +
Transcribed Image Text:The human resource manager at a car dealership wants to know if the ages of its employees are related to the department that they work in. Data was compiled and tabulated in a 2-way contingency table. The employees were classified according to their age and department. Expected count3 are printed below observed counts Saies Accounts Markecing Repairs Total 20-29 10 27 43 88 17.74 26.20 *** 23.62 30-39 29 26 38 22 23.18 26.72 34.24 30.86 40-49 33 32 72 82 219 44.15 50.88 65.20 58.77 50-59 81 106 86 54 327 65.92 75.97 97.36 87.75 Total 151 ** 223 201 749 Chi-Sq - 5.348 + **** + 0.024 + 15.912 +
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