Overview
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Learn how to perform logistic regression using R and Excel. This course shows how to process, analyze, and finalize forecasts and outcomes.
Syllabus
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Introduction
- Welcome
- What you should know
- Exercise files
- The normality assumption
- Recognize abnormal distribution
- Forecast: Too high or too low
- Manage different slopes
- Use of odds instead of probabilities
- Use of odds to limit the probabilities on the upside
- Logs: exponents, bases, sum of logs, and the log of products
- Use of log odds to limit the probabilities on the downside
- Predict the log of the odds, the logit
- Set up the worksheet: Original data and logistic regression coefficients
- Set up the logit column, the antilog column, and the probability column
- Establish the log likelihood and run Solver
- Interpret -2LL or deviance
- Install the mlogit package
- Establish the data frame with XLGetRange
- The mlogit function syntax
- Use of glm instead of mlogit
- Deal with problems introduced by three or more possible outcomes
- Identify long versus wide data frames
- The special mlogit syntax
- Next steps
