Throughout the course of the semester, I have been performing tests in order to answer the research question, “How does household income affect family involvement?” This question comes from research conducted with The Andy Taylor Center and Head Start. These are both child care centers whom we sent activities and surveys in order to better understand family involvement. Three of the tests that were run in order to answer the research question are the ANOVA test, the Regression test and the Chi-squared test. These were conducted using both the R-Studio and SPSS statistical systems.
The independent variable question for the research conducted is, “How involved was your family throughout the activity?” This question could be answered by participants on a scale of 0 to 10 with 0 meaning not at all and 10 meaning a great amount. This question was recoded for some tests due to their being multiple questions involving parent involvement levels and the necessity in order to run the test.
The dependent variable question for the research that was conducted is, “What is your annual household income?” This question could be answered with the categories, “Less than $10,000”, “$31,000 to $50,999”, “$51,000 to $70,999”, “$71,000 to $90,999”, “$91,000 or more” and “Prefer not to answer.” The option of “Prefer not to answer” was missing data and was recoded to not be included in the tests that were conducted.
Table 1.
Chi-squared
| Low Income | High Income | |
| Not Engaged | 4 | 4 |
| Moderate Engagement | 16 | 4 |
| Engaged | 12 | 12 |
| X-squared= 4.68 | df=2 | p-value= .09633 |
This table shows that in the “Not Engaged” category there were four respondents that were in the low income bracket and four respondents that were in the high income bracket. The “Moderate Engagement” category shows that there were 16 respondents in the low income bracket and four respondents in the high income bracket. In the “Engaged” category there were 12 respondents in the low income bracket and 12 respondents in the high income bracket. We also see that the chi-squared statistic is 4.68. The degrees of freedom for this test is 2. The p-value shows us that there is no significant difference at the .05 level. This test was recoded to only include low and high income levels removing the six different categories of answer choices. This test was conducted using R-studio.
Table 2.
Basic Linear Regression
| Estimate | Std. Error | t-value | Pr | |
| Intercept | 7.2241 | 0.7167 | 10.079 | 2.88e-15*** |
| v36 | -0.1034 | 0.1603 | -0.645 | 0.521 |
| R-squared= 0.005917 |
This table shows a Basic Linear regression in R-studio. V36 is standing in place for the dependent variable, “What is your annual household income?” Family involvement has a negative correlation with household income. For every one unit family involvement increases, household income decreases by -0.1034. There is a significant finding at the .001 level. The R-squared statistic is 0.005917 which means that income has explained .59% of the variation in family involvement. This test was conducted using R-studio.
Table 3.
ANOVA
| Sum of squares | df | Mean Square | F | Sig. | |
| Between groups | 255.259 | 6 | 42.543 | 3.773 | .003 |
| Within groups | 687.800 | 61 | 11.275 | ||
| Total | 943.059 | 67 | |||
This is an ANOVA test run in the statistical system SPSS. Family involvement was measured using the question, “How involved was your family throughout the activity?” We can see that the significant value is .003 which below the .01 level and therefore is significant at the .01 level. This means there is a significant difference between the means.
In order to answer the research question, “How does household income affect family involvement?”, these three tests were conducted. The independent variable being family involvement and the dependent variable being household income. In the Chi-squared test we see that there is no significant difference at the .05 level between family involvement and household income. With the Regression test, it shows that family involvement has a negative correlation with household income. Finally, the ANOVA test shows that there is significance at the .01 level for family involvement. Overall, we see that household income does not have a significant effect on household income.