RSCH 6210 WEEK 10 DISCUSSION LATEST-WALDEN

1. RSCH 6210 WEEK 10 DISCUSSION LATEST-WALDEN Visit Below Link, To Download This Course: https://www.tutorialsservice.net/product/rsch-6210-week-10-discussion-latest-walden/ Or Email us on SUPPORT@TUTORIALSSERVICE.NET RSCH 6210 Week 10 Discussion Latest-Walden RSCH6210 RSCH 6210 Week 10 Discussion Latest-Walden 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: 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 Estimate a multiple regression model that answers your research question. Post your response to the following: What is your research question? Interpret the coefficients for the model, specifically commenting on the dummy variable.

2. 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. By Day 5 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. Click on the Reply button below to reveal the textbox for entering your message. Then click on the Submit button to post your message. Download Now