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Specifically 2, 3, 4, amp; 5. I also have some spss data.
The image at the bottom is used to help answer question 2. I also have some spss data. Thanks
AELC 8990
Homework #1
Multiple Regression
A study was carried out to explore the relationship between Aggression and several potential predicting factors in 666 children who had an older sibling. Variables measured were Parenting Style (high score = bad parenting practices), Computer Games (high score = more time spent playing computer games), Television (high score = more time spent watching television), Diet (high score = the child has a good diet low in harmful additives), and Sibling Aggression (high score = more aggression seen in their older sibling). Past research indicated that parenting style and sibling aggression were good predictors of the level of aggression in the younger child. All other variables were treated in an exploratory fashion. The data are in the file Child Aggression.sav. Analyze them with multiple regression.
1. Identify the independent and dependent variables. (5 points)
*Independent Variable - Parenting Style, Computer games, TV, Diet, Sibling aggression.
*Dependent Variable - Aggression
2. Interpret the following statistics for the full regression model. (10 points)
a. R - the correlation coefficient r measures the strength and direction of a linear relationship between two variables on a scatterplot. The value of r is always between +1 and -1.
b. R2 - measures how close the data are to the fitted regression line. It is also known as the coefficient of determination, or the coefficient of multiple determination for multiple regression.
c. 1 - R2 - coefficient of non-determination, the unexplained portion.
d. Partial Regression Coefficients - The partial regression coefficient partial regression weight, slope coefficient or partial slope coeffi- cient. It is used in the context of multiple linear regression (mlr) analysis.
e. Standard error - is the approximate standard deviation of a statistical sample population
3. What strategy did you use to enter the variables into the regression equation? Justify your response. (5 points)
*Used Hierarchically strategy. Entered parenting style and sibling aggression in the first step, then used remaining variable in the second step.
4. Write the regression equation for the full model. What is the predicted value (for the full model) of the dependent variable for children with the following characteristics: (5 points)
a. Parenting Style = .85
b. Computer Games = .34
c. Television = -.75
d. Diet = -.14
e. Sibling Aggression = .07
5. Is the model statistically significant? Yes
Indicate the null hypothesis tested and the decision rule used to reach a decision. (5 points)
6. Which independent variables contribute significantly to the full model? Are there any independent variables that did not contribute significantly to the model and were excluded? (10 points)
*Parenting style significantly predicted aggression
*Sibling aggression significantly predicted aggression
*Computer games significantly predicted aggression
*Good diet significantly predicted aggression
*TV did not significantly predict aggression.
* Based on the standardized beta values, the most substantive predictor of aggression was actually parenting style, followed by computer games, diet and then sibling aggression.
7. Is multicollinearity a problem in the analysis? Explain. (5 points)
*Tolerance values less than .10 and VIF values greater than 10 indicate no multicollinearity.
