To:  sbaker@odu.edu

From:  Thomas Meyer
tmeyer@ph.vccs.edu
276 656-0283
Patrick Henry Community College

Subject:  Statistics - w/  Dr.Spencer Baker - Homework Assignment #4, Ch 15 - Problem 23, page 402.

Date: April 9, 2004

Use the following algorithm:

1.  Get the data

2.  Manipulate the data

To conduct the Chi-square test:

Having loaded the data
Click Analyze menu and choose Descriptive Statistics

select Crosstabs...

Move the variable "Gender of the Participant" into the row;
Move the variable "Current Career Interest" into the column.
Click Statistics and mark Chi-square.
Click Continue box

Click OK.

3.  Do something with the data

Right-click the output
Select copy object
Paste the copied object into FrontPage  (Before you paste the object, right-click and read the "results coach")
Save your work

 

Note:  When the variable you are testing is dichotomous (such as gave blood, did not give blood, is a democrat, isn't a democrat) use the chi-square as a test statistic, or use the binomial distribution.

When the variable you are testing is continuous (such as intelligence, persistance, emotive level, etc.) use the t-test statistic to determine whether outcomes differ from what could have been predicted from chance alone.

 

Question:
Use the SPSS data bank provided with this book to conduct a X2 (chi-square) test of independence analysis of the data contained in the data file career.sav.  Conduct an analysis to answer the question "Are there gender differences (gender; 1 = male, 2 = female) in career interests (interest; 1 = fine arts, 2 = humanities, 3 = social sciences, 4 = biological sciences, 5 = physical sciences and math) among students in grades 7-10?"  Given the result of your analysis, what answer would you provide for this question?

Answer:

From the previous Chi-square table, we note that for the 2-sided chi-square test, the value .023 is less than the traditional alpha value of .05.  Therefore we conclude that there is a difference between males and females in the 7th through 10th grades that would not be explained by chance alone. 

Here are some conclusions:

1.  The females outperformed the males: in fine arts 25 to 19; in humanities 12 to 6; and in social sciences 28 to 22. 

2.  The males outperformed the females: in biological sciences 26 to 25; and in physical sciences and math  27 to 10.   The strongest performances by sex were: in physical sciences and math in which the ratio of male/female performance was 27/10 or 2.7 to 1; and in humanities wherein the female/male performance was 12/6 or 2.0 to 1.  

3.  The sexes were more evenly aligned than either of these stronger ratios in fine arts, in social sciences, and they were nearly evenly matched (26 to 25, male to female) in the biological sciences.

 

filename: StatHW3Ch15Prob23page402TomMeyer.doc

Tom Meyer

Thomas Meyer