5.Assume you are an educational researcher that want to investigate the effects of socioeconomic status (SES), home environment, and school and neighborhood environment on the academic achievement in middle school students. You designed a survey to collect the necessary demographic (SES, home environment, neighborhood environment) data to match it with their standardized test results. Your survey is divided into three parts.

Part 1 includes SES information; parent's education, employment status (currently employed yes or no), income level, and receiving free or reduced lunch at school. In part 2, the questions are regarding the environment at home, time spent watching (playing video games) TV at home, having a TV in their rooms, computer available to do assignments at home, Internet access at home, etc. The last section, part 3, includes questions related to the safety of the neighborhood environment: some examples include if the students walk to school, how safe they feel while walking to and from school, do you feel safe at school? Are there a lot of fights at school? etc.

The purpose of collecting these data was to develop a model that can help to predict academic achievement in middle school children using some of these variables.

1.There are many variables collected in these data. Your first task is to discuss some of the considerations that you must make to determine which variables could or should be included in the model. Be sure to discuss the concept of multicollinearity.

2.How could you measure for multicollinearity? How could you address multicollinearity?

3.If the researcher decides to eliminate several of the independent variables in order to reduce the number, how should the researcher determine which variables are more important than others to include in the model?

4.Assume that the end result included 5 variables that were significant predictors of academic achievement. Then, write the estimated regression equation for the model with all 5 variables.