Quant: Crosstabs in SPSS

The aim of this analysis is to answer the question, if someone was rich, would they continue or stop working on their highest degree earned, gender, and job satisfaction.

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Introduction

The aim of this analysis is to answer the question, if someone was rich, would they continue or stop working on their highest degree earned, gender, and job satisfaction.

Methodology

For this project, the gss.sav file is loaded into SPSS (GSS, n.d.).  The goal is to look at the relationships between the following variables: richwork (being wealthy), sex (demographics of gender), satjob (satisfaction level with the job), and degree (education degree level).   The variable richwork is the dependent variable and the other three variables are considered independent variables for this analysis. To conduct a crosstabs analysis, navigate through Analyze > Descriptive Analytics > Crosstabs.  The variable richwork was placed in the “Row(s)” box, and the other three variables were placed in the “Column(s)” box.  Then on the crosstabs dialog box, “Cells” button was clicked, and under the “Counts” section “Observed” was selected and all three boxes were seleceted under the “Percentages” section. The procedures for this analysis are provided in video tutorial form by Miller (n.d.).  The following output was observed in the next four tables.

Results

Table 1: Cases Processing Summary.

Cases
Valid Missing Total
N Percent N Percent N Percent
IF RICH, CONTINUE OR STOP WORKING * Respondent’s highest degree 625 44.0% 794 56.0% 1419 100.0%
IF RICH, CONTINUE OR STOP WORKING * Respondent’s sex 628 44.3% 791 55.7% 1419 100.0%
IF RICH, CONTINUE OR STOP WORKING * JOB OR HOUSEWORK 624 44.0% 795 56.0% 1419 100.0%

According to Table 1, about 44% (~625) of all cases are valid in all three scenarios and about 56% (~793) had missing data, from a total of 1419 respondents.

Table 2: If rich do people continue or stop working with respondent’s highest degree cross tabulation.

Respondent’s highest degree Total
Less than HS High school Junior college Bachelor Graduate
IF RICH, CONTINUE OR STOP WORKING CONTINUE WORKING Count 52 210 39 84 36 421
% within IF RICH, CONTINUE OR STOP WORKING 12.4% 49.9% 9.3% 20.0% 8.6% 100.0%
% within Respondent’s highest degree 69.3% 64.6% 81.3% 67.2% 69.2% 67.4%
% of Total 8.3% 33.6% 6.2% 13.4% 5.8% 67.4%
STOP WORKING Count 23 115 9 41 16 204
% within IF RICH, CONTINUE OR STOP WORKING 11.3% 56.4% 4.4% 20.1% 7.8% 100.0%
% within Respondent’s highest degree 30.7% 35.4% 18.8% 32.8% 30.8% 32.6%
% of Total 3.7% 18.4% 1.4% 6.6% 2.6% 32.6%
Total Count 75 325 48 125 52 625
% within IF RICH, CONTINUE OR STOP WORKING 12.0% 52.0% 7.7% 20.0% 8.3% 100.0%
% within Respondent’s highest degree 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
% of Total 12.0% 52.0% 7.7% 20.0% 8.3% 100.0%

According to Table 2, with further analysis on whether or not people would continue or stop working, 67.4% would stay, and 32.6% would stop working.  In our data about 12% have less than a high school diploma, 52% have a high school diploma, 7.7% have a gone to junior college, 20% have a bachelor degree and 8.3% have a graduate degree. With further analysis with respect to whether or not people would continue or stop working with respect to the respondent’s highest degree earned, 56.4% of respondents who have only a high school diploma would choose to leave work if they were rich making them the biggest demographic to leave in this “what if” scenario.  Finally, 81.3% of those with a junior college degree would stay at their job if they were rich, making them the biggest demographic to stay in this “what if” scenario. Those with a high school diploma, bachelor degree or graduate degree were approximately 65-69% more likely to continue working if they were rich.

Table 3: If rich do people continue or stop working with respondent’s gender cross tabulation.

Respondent’s sex Total
Male Female
IF RICH, CONTINUE OR STOP WORKING CONTINUE WORKING Count 214 209 423
% within IF RICH, CONTINUE OR STOP WORKING 50.6% 49.4% 100.0%
% within Respondent’s sex 69.3% 65.5% 67.4%
% of Total 34.1% 33.3% 67.4%
STOP WORKING Count 95 110 205
% within IF RICH, CONTINUE OR STOP WORKING 46.3% 53.7% 100.0%
% within Respondent’s sex 30.7% 34.5% 32.6%
% of Total 15.1% 17.5% 32.6%
Total Count 309 319 628
% within IF RICH, CONTINUE OR STOP WORKING 49.2% 50.8% 100.0%
% within Respondent’s sex 100.0% 100.0% 100.0%
% of Total 49.2% 50.8% 100.0%

In our sample data set about 49.2% were male and 50.8% were female, according to Table 3. With further analysis on whether or not people would continue or stop working on the respondent’s gender, 34.5% of women and 30.7% of men would choose to leave work if they were rich.  Gender doesn’t seem to be as strong of an indicator to help determine if a respondent were more likely to continue or stop working if they were rich in this “what if” scenario.

Table 4: If rich would people continue or stop working with respondent’s job satisfaction cross tabulation.

JOB OR HOUSEWORK Total
VERY SATISFIED MOD. SATISFIED A LITTLE DISSAT VERY DISSATISFIED
IF RICH, CONTINUE OR STOP WORKING CONTINUE WORKING Count 199 172 36 14 421
% within IF RICH, CONTINUE OR STOP WORKING 47.3% 40.9% 8.6% 3.3% 100.0%
% within JOB OR HOUSEWORK 71.8% 64.9% 60.0% 63.6% 67.5%
% of Total 31.9% 27.6% 5.8% 2.2% 67.5%
STOP WORKING Count 78 93 24 8 203
% within IF RICH, CONTINUE OR STOP WORKING 38.4% 45.8% 11.8% 3.9% 100.0%
% within JOB OR HOUSEWORK 28.2% 35.1% 40.0% 36.4% 32.5%
% of Total 12.5% 14.9% 3.8% 1.3% 32.5%
Total Count 277 265 60 22 624
% within IF RICH, CONTINUE OR STOP WORKING 44.4% 42.5% 9.6% 3.5% 100.0%
% within JOB OR HOUSEWORK 100.0% 100.0% 100.0% 100.0% 100.0%
% of Total 44.4% 42.5% 9.6% 3.5% 100.0%

In our sample data set about 49.2% were male and 50.8% were female, according to Table 3. With further analysis on whether or not people would continue or stop working on the respondent’s gender, 34.5% of women and 30.7% of menFinally, in Table 4, about 44.4% of respondents are very satisfied at work, 42.5% of respondents are moderately satisfied at work, 3.8% of respondents are moderately dissatisfied at work, and 1.3% of respondents are very dissatisfied at work. With further analysis on whether or not people would continue or stop working on the respondent’s job satisfaction level, 40% of respondents who are moderately dissatisfied would choose to leave work if they were rich making them the biggest demographic to leave in this “what if” scenario. In fact, if the respondents were anything but very satisfied with their job, they had an approximately 7-12% chance increase of wanting to leave their jobs if not rich.  This illustrates that 71.8% of those who are very satisfied with their jobs would stay at their job if they were rich, making them the biggest demographic to stay in this “what if” scenario.

Conclusions

Overall, this analysis has shown that to answer the question, if someone was rich, would they continue or stop working on their highest degree earned, and job satisfaction may have a contributing factor to the respondent’s decision in this “what if” scenario.  However, gender may not play an important role in answering this question.

Would choose to leave work if they were rich.  Gender doesn’t seem to be as strong of an indicator to help determine if a respondent were more likely to continue or stop working if they were rich in this “what if” scenario.

SPSS Code

DATASET NAME DataSet1 WINDOW=FRONT.

CROSSTABS

  /TABLES=richwork BY degree sex satjob

  /FORMAT=AVALUE TABLES

  /CELLS=COUNT ROW COLUMN TOTAL

  /COUNT ROUND CELL.

References:

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