Have some delayed book-chat from April, May, June, July, August and September.

Have some delayed book-chat from April, May, June, July, August and September.

Attention conservation notice: Only relevant if you (1) really care about statistics, and (2) will be in Pittsburgh on Monday. Through a fortuitous concourse of calendars, we will have three outstanding talks on Monday, 14 October 2013. In chronolog...

Lecture 10: Functions in R are objects, just like everything else, and so can be both arguments to and return values of functions, with no special machinery required. Examples from math (especially calculus) of functions with other functions as argum...

In which we use Tukey's rule for identifying outliers as an excuse to learn about debugging and testing. Assignment Introduction to Statistical Computing

In which we continue to practice the arts of debugging and testing, while learning about making our code more general, handling awkward special cases, and pondering what it means to say that an observation is an outlier. Assignment, data, deliberatel...

Lecture 10: Basics from calculus about minima. Taylor series. Gradient descent and Newton's method. Curve-fitting by optimization. Illustrations with optim and nls. R for examples Reading: recipes 13.1 and 13.2 in The R Cookbook; chapters I.1, II.1 a...

Lecture 11: Abstraction as a way to make programming more friendly to human beings. Refactoring as a form of abstraction. The rectification of names. Consolidation of related values into objects. Extracting common operations. Defining general operat...

In which we practice passing functions as arguments to other functions, by way of an introduction to likelihood and its maximization; and, incidentally, work more with plotting in R. Assignment Introduction to Statistical Computing

In which we continue to practice using functions as arguments and as return values, while learning something about the standard error of maximum likelihood estimates, and about the modularity of methods like the jack-knife. Assignment Introductio...

Lecture 12: Design patterns and their benefits: clarity on what is to be done, flexibility about how to do it, ease of adapting others' solutions. The split/apply/combine pattern: divide big structured data sets up into smaller, related parts; apply ...

Lecture 13, Split/apply/combine II: using plyr. Abstracting the split/apply/combine pattern: using a single function to appropriately split up the input, apply the function, and combine the results, depending on the type of input and output data. Sy...

Midterm Exam: eight questions about thirteen lines of code. Introduction to Statistical Computing

Arthur Benjamini says we should teach statistics before calculus. He points out that most of what we do in high school math is preparing us for calculus. He makes the point that while physicists, engineers and economists need calculus, in the … Continue reading →

The only thing is, I’m not sure who’s David here and who is Goliath. From the standpoint of book sales, Gladwell is Goliath for sure. On the other hand, Gladwell’s credibility has been weakened over the years by fights with bigshots such as Steven Pinker. Maybe the best analogy is a boxing match where Gladwell […]The post Gladwell and Chabris, David and Goliath, and science writing as stone soup appeared…

The Area Under the Receiver Operator Curve is a commonly used metric of model performance in machine learning and many other binary classification/prediction problems. The idea is to generate a threshold independent measure of how well a model is able to distinguish between two possible outcomes. Threshold independent here just means that for any model […]

Editor's note: This post is contributed by Debashis Ghosh. Debashis is the chair of the Biostatistical Methods and Research Design (BMRD) study sections at the National Institutes of Health (NIH). BMRD's focus is statistical methodology. I write today to discuss effects of … Continue reading →

Christopher Chabris reviewed the new book by Malcolm Gladwell: One thing “David and Goliath” shows is that Mr. Gladwell has not changed his own strategy, despite serious criticism of his prior work. What he presents are mostly just intriguing possibilities and musings about human behavior, but what his publisher sells them as, and what his […]The post Chris Chabris is irritated by Malcolm Gladwell appeared first on Statistical Modeling, Causal…