Let’s try our goodness of fit tool
Expected count under Benford’s law (Tableau Calculated Field)
sum([Benford Percent]) * TOTAL(sum([N]))
A data frame with columns:
The Chi-Square test is not very powerful. When in fact the the Null Hypothesis is wrong, the test can’t tell it is wrong. All tests can tell the difference with enough samples. Statistical power is a key element in driving a sample size.
You have recently been hired by the U.S. internal revenue service (IRS) to catch corporate cheaters. You have been given three companies to investigate. You will need to decide if the IRS should build a legal case to investigate the institution for fraud.
You will be responsible to report as much evidence as you can with the data provided for each institution above. The government entity has more available data than the other two which will require you to dig deeper to find additional clues.
You can find varied data sources available for your use on the data page in Canvas. You will need to use more than one of the data sets provided but you are not expected to use them all,