Module 2: Regression Analysis: Hypothesis Testing and Goodness of Fit

Using the Regression model to make predictions.Making inferences using the estimated model.ěuilding a Regression Model and estimating it using Excel.The module also introduces the notion of errors, residuals and R-square in a regression model. We will use the estimated model to infer relationships between various variables and use the model to make predictions. We will build a regression model and estimate it using Excel. In this module you will get introduced to the Linear Regression Model. Module 1: Regression Analysis: An Introduction However, it is not standard with earlier versions of Excel for Mac. It is also standard with the 2016 or later Mac version of Excel. Note: This course uses the ‘Data Analysis’ tool box which is standard with the Windows version of Microsoft Excel. The focus of the course is on understanding and application, rather than detailed mathematical derivations. All these are introduced and explained using easy to understand examples in Microsoft Excel. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects. The course introduces you to the very important tool known as Linear Regression.

This is the fourth course in the specialization, 'Business Statistics and Analysis'. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. Regression Analysis is perhaps the single most important Business Statistics tool used in the industry.

Linear regression in excel for mac