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 ...

Your client, Dave’s BBQ, a local independent restaurant, is interested in determining the effect on sales revenue of certain advertising strategies. Dave has weekly data on advertising dollars spent ...

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 ...

After fitting survival data with a linear regression model, it is important to know how to use the results to make prediction of the t-year survival probability or median failure time for future ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. David is comprehensively experienced in many facets of financial ...

Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the ...

Regression analysis refers to a method of mathematically sorting out which variables may have an impact. The importance of regression analysis for a small business is that it helps determine which ...