Regression

Running head: REGRESSION ANALYSIS 1

REGRESSION ANALYSIS 2

Regression Analysis

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Application of regression analysis is a very important role in achieving the success of any business. This analysis involves the identification of the interrelationships between dependent and independent valuable on a particular variable. In a business situation, the managers may choose to use previous data of the company’s sales to conduct regression analysis on the sales performances by having market and demand values as the dependent and independent variables respectively. Application of regression analysis in business is useful in forecasting and optimization in business.

Regression analysis can be useful in predicting the future opportunities of the business. The analysis from the past data on the sales of the company can be used to predict the future purchase of consumers behavior on particular products (Lehrer,2018). The business may opt to understand to what degree market is affecting the sales of the business products, this helps the company understand new techniques and also come up with new inventory levels to improve the quality of products. Regression analysis is also important in the optimization process of the business. Understanding the interconnections between various items helps the company makes the correct decisions about how to ensure the success of the business and maximize its profits. This understanding helps the business make the best from its sales by utilizing opportunities and taking risks in the sale of products.

Regression analysis plays a major role in statistical models. To begin with, regression analysis helps in indicating the significant interrelationship and strength impact of the independent and dependent variables (Fiorito, 2018). Through regression analysis conclusions can be made on how different variables are connected, for example, analysis on the number of accidents can be analyzed by considering the number of cars driven at high speeds and the number of cars on the road. These analyses also help in understanding the impact or to what degree of effect does the caused from the variable

References

Fiorito, S. (2018). Variable importance in modern regression with application to supplier productivity analysis (Doctoral dissertation, Politecnico di Torino).

Lehrer, M., Bhadra, A., Aithala, S., Ravikumar, V., Zheng, Y., Dogan, B., ... & Whitman, G. J. (2018). High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma. Oncoscience, 5(1-2), 39.