Writing Homework Help

You are interested in exploring whether gender [SEX] or social class [CLASS] differences exist in Americans’ views about the impact of a mother working on her children. The GSS 2018 asked respondents the degree to which they agreed or disagreed with the statement, “preschool age children suffer if mothers work” [FEPRESCH].

You are going to do two chi square tests at the .05 alpha level as all the variables are categorical (or discrete).

Step 1. State the 2 null and alternative hypotheses. [Remember with chi square the alternative hypothesis is always stated non-directionally.]

Step 2. Run the SPSS analyses

Let’s look at the relationship between SEX and FEPRESCH first.

• From the SPSS menu baràAnalyzeàDescriptiveàCrosstabs.
• In the Crosstabs Dialog BoxàPut the independent variable—SEX—in the Row Box.
• Now put the dependent variable—FEPRESCH—in the Column Box.
• CLICKàSTATISTICS, then in the Statistics Dialog Box, then CLICKàCHI SQUARE.
• CLICKà CONTINUE (this returns you to the Crosstabs dialog box.)
• CLICKàCELLS, this opens the Cells dialog box. We are ALWAYS most interested in learning about the independent variable or ROW. Under percentages, CLICKà ROWS. Under counts, CLICKàOBSERVED and EXPECTED options. CLICKà CONTINUE (this returns you to the Dialog box).
• CLICKàOK

Step 3: Replace SEX with CLASS and repeat the chi square test. [Remember to figure out which is the independent variable and which is the dependent variable.]

Step 4: Interpret the output and write up the Results

1. First, check to make sure the expected frequencies did not exceed 25% of the cells – the criterion for appropriate use of the chi square test statistic.
2. Create a table to report the results of the chi-square for sex X fepresch, including the %s from the crosstab, and the relevant statistical information (X2 value, df, p value).

Write up the results of each hypothesis separately. In doing so, be sure to provide support/evidence for your decision about rejecting or retaining the null hypothesis, including providing x² value, df, and p-value. Also, report percentages so that the reader can understand the specific nature of the differences (or lack of differences) between the independent variable’s groups (i.e., value categories).

An example for a write-up and table to report the results of a chi square test can be found in this week’s content. Refer also to the articles that feature chi-square for an example of how this can be done.

On separate page included work from spss and the data set to use is : https://www.studypool.com/discuss/download?id=2188…