![]() You would like to show progress, so you decide to include them in your report to management. Your company has no business in Ohio or Louisiana, and it there is no reasonable conclusion why these correlations exist, even though the p-values are less than 5%. Of the 100, two show statistical significance: interest rates on boat loans in south Louisiana and household debt in north Ohio. The process of data mining involves automatically testing huge numbers of hypotheses about a single data set by exhaustively searching for combinations of variables that might show a correlation. You download a database from a government website and decide to run a series of automated regressions. Data Dredging (from Wikipedia) Data dredging (data fishing, data snooping, equation fitting) is the use of data mining to uncover relationships in data. Imagine that instead of choosing only four macroeconomic indicators, you chose 100. This approach to data can be useful in creating. This could have gone another way…īUT wait! This could have gone another way. Data dredging, also known as data fishing or data mining, is a post hoc analysis of outcomes data. An honest analyst would not make this claim, but show that there is no relationship. You had conflicting evidence of the statistical significance of two correlations, but since one side of the evidence supports a personal claim you would like to make, you decide to accept it. Since you’re in a bind, you decide to claim that GDP and Employment rate have a strong relationship to revenue, and that you’re going to explore this further. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |