### Lecture: Regression: Predicting and Relating Quantitative Features (Advanced Data Analysis from an Elementary Point of View)

Statistics is the branch of mathematical engineering which designs and
analyzes methods for learning from imperfect data. Regression is a statistical
model of functional relationships between variables. Getting relationships
right means being able to predict well. The least-squares optimal prediction
is the expectation value; the conditional expectation function is the
regression function. The regression function must be estimated from data; the
bias-variance trade-off controls this estimation. Ordinary least squares
revisited as a smoothing method. Other linear smoothers: nearest-neighbor
averaging, kernel-weighted averaging.

*Reading*: Notes, chapter 1 (`examples.dat` for running example; `ckm.csv` data set for optional exercises)

Advanced Data Analysis from an Elementary Point of View

Posted at January 16, 2013 23:15 | permanent link