Regression is a very widely used statistical technique for management (among oth
ID: 2908718 • Letter: R
Question
Regression is a very widely used statistical technique for management (among others) to make important business decisions. This is the study of relationships between one or more variables. One compares dependent variables (y) and independent variables (x) to attempt to describe and predict the best possible outcomes. If you look in chapter 13 at the Tasty Sub examples 13.1 on page 465 a these give a good idea of the use of simple regression. In chapter 13 yearly revenues are affected (dependent) on population size as indicated on page 466 Multiple regression uses more than one independent variable (x) which is a better predicator for examples like what effects the sale price of a house, is not only affected by historical prices but also by comparing crime statics, comparable selling prices, school district and other factors. This makes multiple regression a little more useful than simple regression and example 14.1 on 525and in chapter 14 they not only use population size but also business ratings to provide a better relationship on revenues. Please provide and discuss another example of regression (simple or multiple) and how it can be used in the real world.
Explanation / Answer
Suppose you have a lemonade business. A simple linear regression could mean you finding a relationship between the revenue and temperature, with revenue as the dependent variable. In case of multiple variable regression, you can find the relationship between temperature, pricing and number of workers to the revenue. Thus, regression analysis can analyze the impact of varied factors on business sales and profits.