In this week’s brief we feature a guest blog on Ethical Data Science; our course spotlight is:
- July 17 – Aug 14: Logistic Regression
See you in class!
Founder, Author, and Senior Scientist
Ethical Data Science
As data science has evolved into AI, the intimate connection between the scientist and the data is growing distant. As black-box models, with their superior predictive power, increasingly dominate, the modeler’s ability to recognize and avoid harmful and even illegal […]
Word of the Week
In logistic regression, a squashing function takes the output of a logit model, which produces odds, and “squashes” it so that it fits in the range between 0 and 1 and can be interpreted as a probability.
Joseph Hilbe, a prolific author in the field of statistical modeling, taught a number of Statistics.com courses right up until his death, just over 3 years ago. In addition to his numerous contributions in statistics, Joe had an abiding interest in astrostatistics and would happily show any visitor his treasured collection of […]
Logistic Regression (July 17 – Aug 14)
Developed by Joseph Hilbe and now taught by James Hardin, this course covers:
- How to specify when a logistic regression model is used, and its form
- How to fit a logistic model
- Using information criteria to assess model performance
- Dealing with risk factors, confounders, effect modifiers, interactions
- Dealing with excessive dispersion
Spatial Statistics for GIS Using R (July 10 – Aug 7)
In this course, you will learn how to:
- Describe spatial data using maps
- Describe and implement the ways spatial data is represented in R
- Use spastat to analyze patterns in point data, and detect non-randomness
- Use spdep to analyze patterns in area data, and measure spatial autocorrelation in lattice data
- Use gstat to analyze continuous field data and create contour maps
Your instructor is Prof. Dave Unwin, co-author of Geographic Information Analysis (Wiley), and a variety of other books on this topic.
See you in class!
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