June 16: Statistics in Practice

Statistics in Practice

In this week’s brief we feature a guest blog on Ethical Data Science; our course spotlight is:

See you in class!

Peter Bruce
Founder, Author, and Senior Scientist

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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

Squashing Function

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.

Instructor Spotlight

Joseph Hilbe

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 […]

Course Spotlights

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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Financial Risk Modeling

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