In a fuzzy regression discontinuity (RD) design, the probability of treatment jumps when a running variable (R) passes a threshold (R0). Fuzzy RD estimates are obtained via a procedure analogous to ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model.

For example, you might want to predict an employee's salary based on age, height, high school grade point average, and so on. There are approximately a dozen common regression techniques. The most ...

In the worked example we already considered above, if we run the multiple linear regression, we would generate a 95% confidence interval (CI) around the regression coefficient for age, which is a ...

A regression equation with a zillion dummy variables in it is hard to read and has little generalizable business value. For example, instead of having a factor “city” with many different levels/values ...

Multiple linear regression is a classical statistics technique that predicts a single numeric value from two or more numeric predictor variables, for example, predicting income from age and height.