What are some of the pitfalls and limitations of regression and correlation analysis and how might they impact a business decision?

Business & Finance homework help| Business & Finance homework help

Correlation analysis and regression are both powerful tools that can help you to predict future outcomes and assess the relationships between variables. If not considered, these techniques can lead to poor business decisions.

Multicollinearity is the most frequent limitation. This occurs when multiple explanatory variables are in a close relationship to each other. It can cause less reliable results as it might be hard to identify which variable has what causal effect on another. Additionally, regression models are only as good as the data that they use – meaning any errors in the data set (such as outliers or missing values) could potentially lead towards inaccurate results if not addressed properly.

The regression model assumes linearity of variables. However, real world scenarios are often complex and involve systems with relationships that vary across time or between contexts. This means that while regression/correlation analysis can provide useful insights into certain types of problems, relying solely on them without taking into account other factors may not always produce accurate results especially when dealing with complex decision making situations. Businesses should be cautious when using regression/correlation analysis to make informed decisions.

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