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Material Type: Assignment; Class: Computer Data Analysis; Subject: Psychology; University: University of La Verne; Term: Unknown 1989;
Typology: Assignments
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PSY/BHV 395 Name: Chapter 7 In-class assignment Define the following terms:
Adjusted R-Square Degrees of Freedom Dummy Variables Intercept
Outliers Residuals Spurious Factors
To create a bivariate linear regression:
To graph the regression line using the output from our analyses of the linear regression:
PSY/BHV 395 Name: Chapter 7 In-class assignment Hypothesis 1: Teen birth rate is positively associated with poverty. IV: PVS Hypothesis 2: Teen birth rate is negatively associated with expenditures per pupil. IV: SCS Hypothesis 3: Teen birth rate is positively associated with the unemployment rate. IV EMS Hypothesis 4: Teen birth rate is positively associated with the amount of “temporary assistance To needy family” a family receives. IV: PVS
To test the hypotheses (Hypotheses 1 to 4) stated on page 139:
The hypothesis that teen birth rate is positively associated with poverty was supported. Multiple linear regression analysis showed that there is a significant positive relationship, such that states with higher pove rty rates will have higher teen births.
The hypothesis that teen birth rate is negatively associated with expenditures per pupil was not supported. Multiple linear regression analysis showed that there is no significant relationship between these two variables.
The hypothesis that high unemployment rates are related to high teen birth rates is not supported. Multiple linear regression analysis showed that there is no significant relationship between these two variables.
The hypothesis that the more a state spends on a needy family the higher the teen birth rate was not supported, however, there was a significant relationship between these two variables as indicated by a multiple linear regression analysis. In this sample, the more a state spent on a needy family, the lower the teen birth rate.
How good is the model of the 4 independent variables and their effect on the dependent variable? Adjusted R-Square = .594 or 59.4% variation in the teen birth rate can be explained by the four variables.