Estimating Models Using Dummy Variables Discussion

Week 10 Discussion

Estimating Models Using Dummy Variables – You have had plenty of opportunity to interpret coefficients for metric variables in regression models. Using and interpreting categorical variables takes just a little bit of extra practice. In this Discussion, you will have the opportunity to practice how to recode categorical variables so they can be used in a regression model and how to properly interpret the coefficients. Additionally, you will gain some practice in running diagnostics and identifying any potential problems with the model.

To prepare for this Discussion ON Estimating Models Using Dummy Variables:

Review Warner’s Chapter 12 and Chapter 2 of the Wagner course text and the media program found in this week’s Learning Resources and consider the use of dummy variables.

Create a research question using the General Social Survey dataset that can be answered by multiple regression. Using the SPSS software, choose a categorical variable to dummy code as one of your predictor variables.

By Day 3 of Estimating Models Using Dummy Variables

Estimate a multiple regression model that answers your research question. Post your response to the following:

  1. What is your research question?
  2. Interpret the coefficients for the model, specifically commenting on the dummy variable.
  3. Run diagnostics for the regression model. Does the model meet all of the assumptions? Be sure and comment on what assumptions were not met and the possible implications. Is there any possible remedy for one the assumption violations?

Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

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By Day 5 of Estimating Models Using Dummy Variables

Respond to at least one of your colleagues’ posts and provide a constructive comment on their assessment of diagnostics.

  • Were all assumptions tested for?
  • Are there some violations that the model might be robust against? Why or why not?
  • Explain and provide any additional resources (i.e., web links, articles, etc.) to provide your colleague with addressing diagnostic issues.

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Week 1 Discussion – Categorical Data Analysis

As with the previous week’s Discussion, this Discussion assists in solidifying your understanding of statistical testing by engaging in some data analysis. This week you will once again work with a real, secondary dataset to construct a research question, perform categorical data analysis that answers the question, and interpret the results.

Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another.

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To prepare for this Discussion:

Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.

Create a research question using the General Social Survey dataset that can be answered using categorical analysis.

By Day 3

Use SPSS to answer the research question. Post your response to the following:

  1. What is your research question?
  2. What is the null hypothesis for your question?
  3. What research design would align with this question?
  4. What dependent variable was used and how is it measured?
  5. What independent variable is used and how is it measured?
  6. If you found significance, what is the strength of the effect?
  7. Explain your results for a lay audience and further explain what the answer is to your research question.

Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

By Day 5

Respond to at least one of your colleagues’ posts and comment on the following:

  • Do you think the variables are appropriately used? Why or why not?
  • Does the analysis answer the research question? Be sure and provide constructive and helpful comments for possible improvement.
  • As a lay reader, were you able to understand the results and their implications? Why or why not?

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