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) The table below shows the number of vacation days taken by each respondent in

ID: 3363513 • Letter: #

Question

) The table below shows the number of vacation days taken by each respondent in the previous 90 days and their reported their level of happiness. For example, 9 people took no vacation days and reported being very happy. The respondents were taken from a random sample of n = 351 people.

Vacation days taken in last 90 days

0

1

2

3

4

5+

Very Happy

9 (9.76)

15 (14.05)

20 (21.47)

25 (25.37)

31 (31.23)

37 (35.13)

137

Fairly Happy

5 (12.25)

8 (17.64)

26 (26.95)

35 (31.85)

48 (39.2)

50 (44.1)

172

Not Very Happy

6 (1.5)

6 (2.15)

4 (3.29)

2 (3.89)

1 (4.79)

2 (5.38)

21

Not Happy

5 (1.5)

7 (2.15)

5 (3.29)

3 (3.89)

0 (4.79)

1 (5.38)

21

25

36

55

65

80

90

351

You can see that the chi-square test is not appropriate here because some expected cell counts are less than 5.

To do the hypothesis test to determine if there is an association between happiness and number of vacation days taken in the last 90 days, you will need to merge the data somehow to get large enough expected counts. You can merge categories down and/or across. Draw your new table with observed and expected counts below. There are numerous tables that can be constructed, but you will have to find one which gives a df of at least 3. If you combine too many so that your df = 1 or 2, then you have lost more data than is necessary.

Then do the test, using a significance level of 0.05.

A. Hypothesize:

H0:

Ha:

B. Prepare: = 0.05

     Check the Central Limit Theory Conditions:

C. Compute to Compare: Use your calculator to find the test statistic and the p-value. Draw the distribution labeling the critical region(s) with ²*.

D. Interpret. Give your conclusion and statement.

Vacation days taken in last 90 days

0

1

2

3

4

5+

Very Happy

9 (9.76)

15 (14.05)

20 (21.47)

25 (25.37)

31 (31.23)

37 (35.13)

137

Fairly Happy

5 (12.25)

8 (17.64)

26 (26.95)

35 (31.85)

48 (39.2)

50 (44.1)

172

Not Very Happy

6 (1.5)

6 (2.15)

4 (3.29)

2 (3.89)

1 (4.79)

2 (5.38)

21

Not Happy

5 (1.5)

7 (2.15)

5 (3.29)

3 (3.89)

0 (4.79)

1 (5.38)

21

25

36

55

65

80

90

351

Explanation / Answer

Result:

To do the hypothesis test to determine if there is an association between happiness and number of vacation days taken in the last 90 days, you will need to merge the data somehow to get large enough expected counts. You can merge categories down and/or across. Draw your new table with observed and expected counts below. There are numerous tables that can be constructed, but you will have to find one which gives a df of at least 3. If you combine too many so that your df = 1 or 2, then you have lost more data than is necessary.

Then do the test, using a significance level of 0.05.

0-1

2

3

4+

Total

Very Happy

Observed

24

20

25

68

137

Expected

23.81

21.47

25.37

66.35

137.00

Fairly Happy

Observed

13

26

35

98

172

Expected

29.89

26.95

31.85

83.30

172.00

Not Very Happy, Not happy

Observed

24

9

5

4

42

Expected

7.30

6.58

7.78

20.34

42.00

Total

Observed

61

55

65

170

351

Expected

61.00

55.00

65.00

170.00

351.00

A. Hypothesize:

H0: there is no association between happiness and number of vacation days taken in the last 90 days

Ha: there is association between happiness and number of vacation days taken in the last 90 days

B. Prepare: = 0.05

     Check the Central Limit Theory Conditions:

Critical chi square = 12.59 at 0.05 level.

C. Compute to Compare: Use your calculator to find the test statistic and the p-value. Draw the distribution labeling the critical region(s) with ²*.

  

Col 1

Col 2

Col 3

Col 4

Total

Row 1

Observed

24

20

25

68

137

Expected

23.81

21.47

25.37

66.35

137.00

(O - E)² / E

0.00

0.10

0.01

0.04

0.15

Row 2

Observed

13

26

35

98

172

Expected

29.89

26.95

31.85

83.30

172.00

(O - E)² / E

9.55

0.03

0.31

2.59

12.48

Row 3

Observed

24

9

5

4

42

Expected

7.30

6.58

7.78

20.34

42.00

(O - E)² / E

38.21

0.89

0.99

13.13

53.22

Total

Observed

61

55

65

170

351

Expected

61.00

55.00

65.00

170.00

351.00

(O - E)² / E

47.76

1.02

1.31

15.76

65.85

65.85

chi-square

6

df

2.89E-12

p-value

Calculated chi square = 65.85 > 12.59, the critical value.

Ho is rejected.

D. Interpret. Give your conclusion and statement.

We conclude that there is significant association between happiness and number of vacation days taken in the last 90 days.

0-1

2

3

4+

Total

Very Happy

Observed

24

20

25

68

137

Expected

23.81

21.47

25.37

66.35

137.00

Fairly Happy

Observed

13

26

35

98

172

Expected

29.89

26.95

31.85

83.30

172.00

Not Very Happy, Not happy

Observed

24

9

5

4

42

Expected

7.30

6.58

7.78

20.34

42.00

Total

Observed

61

55

65

170

351

Expected

61.00

55.00

65.00

170.00

351.00