The difference between linear and logistic regression

Post A (84 points): Pretend you are a guest lecturer for an undergraduate statistics course. Your objective is to explain (1) the difference between linear and logistic regression and (s) how to interpret linear and logistic regression coefficients. 1.Linear and Logistic Regression 1. Describe the characteristics of linear and logistic regression analyses. — 15 points 2. Provide examples of variables (include the level of measurement and variables for which data may actually be collected) that could be used for the dependent and independent variables of each regression type. Here’s an example (which means you cannot use this one). For linear regression, one would use ratio data from a variable such as body mass index (BMI) for the dependent variable and one could use nominal data from a variable such as gender for the independent variable. — 10 points 2. Interpretation 1. Explain the difference in how one would interpret simple linear and logistic regression analyses versus multiple linear and logistic regression analyses. — 20 points 2. Provide examples NOT given in the text of how to state null and alternative hypotheses for a linear regression analysis and a logistic regression analysis. — 10 points 3. Find an example of either the use of linear or logistic regression models in a research article in the Journal of Clinical Nursing from this calendar year. Post the citation for your peers using APA 6th Ed. format. Write a brief interpretation of the regression analysis presented in the article. Make sure the article really uses logistic or linear regression analyses. If you do a search using these terms and do not examine the methods and results, you may not find what you need. — 25 points 4. Discuss what you learned while preparing your text for this discussion. What did you already know? What was new to you? — 4 points.




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