Connect the Dots: Linear and Logistic Regression in Excel, Python and R

Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

This course will teach you how to build robust linear models in Excel, R and Python.

Let’s parse that.

Robust linear models : Linear Regression is a powerful method for quantifying the cause and effect relationships that affect different phenomena in the world around us. This course will teach you how to build robust linear models that will stand up to scrutiny when you apply them to real world situations.

Excel, R and Python : Put what you've learnt into practice. Leverage these powerful analytical tools to build a model for stock returns.

What's covered?

Simple Regression :

• Method of least squares, Explaining variance, Forecasting an outcome
• Residuals, assumptions about residuals
• Implement simple regression in Excel, R and Python
• Interpret regression results and avoid common pitfalls

Multiple Regression :

• Implement Multiple regression in Excel, R and Python
• Introduce a categorical variable

Logistic Regression

Talk to us!

• Mail us about anything - anything! - and we will always reply :-)