# Connect the Dots: Linear and Logistic Regression [Video]

 Learn Build robust linear models that stand up to scrutiny in Excel, R and Python Use simple and multiple regression to explain variance Use simple and multiple regression to predict an outcome Interpret the results of a regression Understand the risks involved in regression and avoid common pitfalls This course will teach you how to build robust linear models and do logistic regression in Excel, R and Python. Letâ€™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. Logistic regression: Logistic regression has many cool applications: analyzing consequences of past events, allocating resources, solving binary classification problems using machine learning and so on. This course will help you understand the intuition behind logistic regression and how to solve it using cookie-cutter techniques. Excel, R and Python: Put what you've learnt into practice. Leverage these powerful analytical tools to build models for stock returns. Style and Approach A 5-hour course with good, understandable, explanation with examples as usual for the Loony style. You won't be calculating the stuff by hand after, it is not that detailed, but it gives a useful understanding to be able to apply the tools 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 Implement Multiple regression in Excel, R and Python Introduce a categorical variable Applications of Logistic Regression, the link to Linear Regression and Machine Learning Solving logistic regression using Maximum Likelihood Estimation and Linear Regression Extending Binomial Logistic Regression to Multinomial Logistic Regression Implement Logistic regression to build a model stock price movements in Excel, R and Python 4 hours 45 minutes 9781788991957 16 Dec 2017