During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and profit, and information about clients. Companies often seek out employees with ...

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 ...

Please note: This item is from our archives and was published in 2021. It is provided for historical reference. The content may be out of date and links may no longer function. When teaching cost ...

In this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as: 1) How to use the F-test to determine if your ...

The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

Omitted variable bias can affect treatment effect estimates obtained from observational data due to the lack of random assignment to treatment groups. Sensitivity analyses adjust these estimates to ...

It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...

Recently linear rank statistics with censored data have been used as the estimating functions for the regression parameters in the linear model with an unspecified ...

When you perform regression analysis in Microsoft Excel, you are engaging in a statistical process that helps you understand the relationship between variables. This technique is particularly useful ...