Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

Some models, such as linear regression, are easily interpretable ... and implementing them on simulated and real data in R. You will complete a proctored exam worth 20% of your grade made up of ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

Linear regression attempts to estimate a line that best fits the data (a line ... coefficient. The R-squared number in this example is 68.7%. This shows how well our model predicts or forecasts ...

A method commonly used to fit non-linear curves to data instead of straight regression lines is polynomial regression. This method uses the same principles as linear regression but models the ...

For electronics, linear regression has many applications, including interpreting sensor data. You might also use it to generalize a batch of unknown components, for example.