I’m trying to study for my Statistics course and I need some help to understand this question.

Post a total of 3 substantive responses over 2 separate days for full participation. This includes your initial post and 2 replies to other students.

Due Thursday

Respond to the following in a minimum of 175 words:

This week, we learn about regression analysis and regression “models’. Discuss the role of regression analysis in business by using examples of how these models might work to make predictions. In your discussion, consider the various components of the output and how it might be of value to understanding the data.

Due Monday

According to Black (2017), the concept of regression analysis refers to the development of a model that uses one or more variables to determine another variable. Simple regression assumes a linear relationship between the predetermined independent variable and the dependent variable that is going to be predicted, while a multiple regression model can be used for both nonlinear relationships and multiple independent variables.

For simple regression analysis, an example that comes to mind which is similar to the passenger airplane scenario is shipping packages, where cost is based on the weight of the package (assuming the packaging used for the shipment is a standard size). The cost for transportation of a package would increase as the weight increased, because more fuel is required to transport the weight of the package. A shipping company would need to use this information through simple regression analysis for determining its rate schedule, as it would need to ensure that sufficient revenue was earned to cover the increased cost of a heavier shipment.

For an example of multiple regression analysis, I would continue with the shipment scenario, where the package’s weight determines the cost of transportation. A second independent variable which could be added to the example is size, where the shipping company can transport fewer heavy shipments in large containers versus more heavy shipments in smaller containers. In this case, both independent variables would have an impact on the transportation capacity which the carrier has.

References:

Black, K. (2017). Business Statistics: For Contemporary Decision Making, (9th Edition). Hoboken, NJ: Wiley

AND THIS ONE:

Marcus, great comments and examples to share with the class.

To add, regression analysis involves an equation of two variables where one variable is based on another variable (Lind, Marchal, & Wathen, 2015). Data is gathered and researched to determine which data best relates to the line of the regression equation (Lind, Marchal, & Wathen, 2015). Researchers also research estimates of errors and intervals of confidence and prediction (Lind, Marchal, & Wathen, 2015). The two variables are classified as X (the independent variable) and Y (the dependent variable). The regression equation is as follows: Y = a + bX (Lind, Marchal, & Wathen, 2015).

Lind, D., Marchal, W. & S. Wathen. (2015). Statistical techniques in business and economics. (15 ed.). New York, NY: McGraw-Hill Companies.