regression project 1

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checkpoint

1

For this checkpoint please submit the following three items:

1. A visual representation of your complete model as we have been discussing in class (e.g., please identify what your ultimate outcome variable is as well as the independent and moderating variables). This is the picture with the variable names and arrows.

2. A written description of your model. This is your discussion of what you are looking to find (e.g., number of cans of cola sold) based upon your independent and moderating variables (e.g., emotional ads influence liking which in turn influence purchase quantity). Remember to incorporate several independent and moderating variables so that you have different analysis options.

3. A description of the data source(s) you will use for your model. If you do not have access to appropriate data, then you will not be able to analyze your model!

This assignment is due by Friday 9/21 at 11:59 pm. Late assignments will NOT be accepted. This assignment is a checkpoint assignment as stated in the syllabus, which means that I will grade you based upon completeness and thoroughness. I will provide you with feedback for incorporation for your final project.

checkpoint2

For this checkpoint, please pick two variables from the model you described in checkpoint 1. Classify one of these variables as the dependent variable and one of them as the independent variable. Both of these variables should be continuous.

1. Regress your independent variable on your dependent variable as discussed in your text and shown in class.

2. Identify your R-squared and discuss its meaning in terms of your model.

3. Identify your standard error of estimate and discuss its meaning in terms of your model.

4. Write a regression equation based upon your output

Please be sure to attach your output along with your answers

checkpoint3

Using your dataset for your chosen model, please do the following:

1. Propose a model that specifies a relationship between a minimum of two IVs explaining/predicting one DV (as we have done in class). Please be sure that your chosen IVs for this scenario are continuous.

2. Perform a multiple regression of your IVs on your DV. Be sure to identify which variables are which.

3. Discuss the R-squared and significance of the unrestricted model (i.e., the full model).

4. Specify the slope coefficients for each of your IVs in the model. Describe whether or not each coefficient is significant in your model (i.e., perform the individual hypothesis tests).

5. If you have a non-significant coefficient in step 4, remove the variable(s) from the equation and run your regression again without the variable(s).

5. Write your regression equation (using your variable names, NOT X & Y) for the fully specified model.

6. If you ran a second model without the non-significant variable(s), write this regression equation.

7. Briefly discuss your model and what it means in light of your analyses.

Please note: This assignment is due by 11:59 pm on Friday, 11/2

 
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