Advantages and disadvantages of regression analysis
Answers
Regression analysis, a statistical analysis technique used by economists and business researchers, helps managers and business owners forecast future conditions, lend quantitative support to managers' judgement, point out flaws in management thinking and provide new insights that can help company decision makers move ...
Disadvantages of Multiple Regression
Any disadvantage of using a multiple regression model usually comes down to the data being used. Two examples of this are using incomplete data and falsely concluding that a correlation is a causation.
When reviewing the price of homes, for example, suppose the real estate agent looked at only 10 homes, seven of which were purchased by young parents. In this case, the relationship between the proximity of schools may lead her to believe that this had an effect on the sale price for all homes being sold in the community. This illustrates the pitfalls of incomplete data. Had she used a larger sample, she could have found that, out of 100 homes sold, only ten percent of the home values were related to a school's proximity. If she had used the buyers' ages as a predictor value, she could have found that younger buyers were willing to pay more for homes in the community than older buyers.
In the example of management salaries, suppose there was one outlier who had a smaller budget, less seniority and with fewer personnel to manage but was making more than anyone else. The HR manager could look at the data and conclude that this individual is being overpaid. However, this conclusion would be erroneous if he didn't take into account that this manager was in charge of the company's website and had a highly coveted skillset in network security.
Regression analysis
Explanation:
Advantages
The regression method of forecasting is used for, as the name implies, forecasting and finding the causal relationship between variables
Regression method of forecasting can help a small business, and indeed any business that can impact its success in the coming weeks, months and years into the future.
Disadvantages
- It is limited to the linear relationship
- It is easily affected by outliers
- regression solution will be likely dense (because no regularization is applied)
- regression solutions obtained by different methods (e.g. optimization, least-square, QR decomposition, etc.) are not necessarily unique.”
#Learn more :
https://brainly.in/question/12496912