I need help setting this up in an SPSS dataset. The rest I can do... A psycholog
ID: 3173838 • Letter: I
Question
I need help setting this up in an SPSS dataset. The rest I can do...
A psychology student at a university is curious whether students in different majors have different class time preferences, or whether class time preference is independent of major. After doing some preliminary research, she chooses three different majors and recruits 10 volunteers from each major. She then asks them to choose their preferred class time—either morning or afternoon. The results are listed below. Perform a chi square test of independence (using an SPSS two-way contingency table analysis) to determine whether the proportions of class time preferences are the same or different across the major fields of study. Use the weighted cases method.
The steps will be the same as the ones you have been practicing in Part One of the assignment—the only difference is that you are now responsible for creating the data file as well. Remember to name and define your variables under the “Variable View,” then return to the “Data View” to enter the data.
Morning
Afternoon
TOTAL
Engineering
3
7
10
Psychology
6
4
10
Business
5
5
10
TOTAL
14
16
30
Morning
Afternoon
TOTAL
Engineering
3
7
10
Psychology
6
4
10
Business
5
5
10
TOTAL
14
16
30
Explanation / Answer
Solution:-
State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.
H0: Class time preferences and major fields of study are independent.
Ha: Class time preferences and major fields of study are not independent.
Formulate an analysis plan. For this analysis, the significance level is 0.05. Using sample data, we will conduct a chi-square test for independence.
Analyze sample data. Applying the chi-square test for independence to sample data, we compute the degrees of freedom, the expected frequency counts, and the chi-square test statistic. Based on the chi-square statistic and the degrees of freedom, we determine the P-value.
DF = (r - 1) * (c - 1) = (2 - 1) * (3 - 1)
D.F = 3
Er,c = (nr * nc) / n
E1,1 = (14 * 10) /30 = 4.667
E1,2 = (16*10) / 30 = 5.33
E2,1 = (14 * 10) / 30 = 4.667
E2,2 = (16 * 10) / 30 = 5.33
E3,1 = (14 * 10) / 30 = 4.667
E3,2 = (16 * 10) / 30 = 5.33
2 = [ (Or,c - Er,c)2 / Er,c ]
2 = (3 - 4.667)2/4.667 + (7 - 5.333)2/5.333 + (6 - 4.667)2/4.667 + (4 - 5.333)2/5.333 + (5 - 4.667)2/4.667 + (5 - 5.333)2/5.333
2 = 0.5953 + 0.52086 + 0.3803 + 0.3334 + 0.0237 + 0.2079
2 = 1.8744
where DF is the degrees of freedom.
We use the Chi-Square Distribution Calculator to find P(2 > 1.8744) = 0.59
Interpret results. Since the P-value (0.59) is greater than the significance level (0.05), we have to accept the null hypothesis.
Thus, we conclude that we have sufficient evidence in the favor of the claim that Class time preferences and major fields of study are independent.
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