A regression analysis is pertinent to finding trends and making business decisions

A regression analysis is pertinent to finding trends and making business decisions

A regression analysis is pertinent to finding trends and making business decisions. When two or more variables have relationships, their strengths can be determined. This statistical measure is great for investments and the finding and understanding price. An example of a regression analysis is a government study. The data from this case was collected between the years of 1990 and 1994. The purpose of this case was to “build a model that predicts domestic immigration or to answer the question of why do people leave one place to go to another?” (Chatterjee & Hadi, 2015, p.6). The data set was 48 states excluding Alaska and Hawaii given their climate their drastic climate differences. The response variable or dependent variable is “net domestic immigration” and the independent variable are “unemployment, wage, crime, income, temperature, education, region, business failure, taxes and poverty” (Chatterjee & Hadi, 2015, p.6). The method was used the o determine the correlation between immigration and outside factors. They used a multiple regression analysis. Their analysis highlights that Idaho is the state with the highest correlation to the net domestic immigration of 71.41. The concepts and conclusions, in this case, are similar to the concepts in the book. The correlation matrix is identical to the concept and example in the text. Overall, the concept of regression serves a huge purpose in business. Testing the strength of relationships can affect the strategic management style. A regression analysis can allow a company to increase their competitive position in a market.

References

Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. John Wiley & Sons

……………………………Answer preview………………………..

I concur with the author that the regression analysis is one of the most purposeful tools for managers as it helps study business trends and enable forecasting. More so, it is the most preferred model since its techniques like the scatter and high-low graphs provide overall superior results compared to other models (Kleinbaum, Kupper, Nizam, & Muller, 2007)………………………….

APA

391 words

Get instant access to the full solution from yourhomeworksolutions by clicking the purchase button below