Chi Squared Testing (#14)

In the Lean and Six Sigma methodologies, a Chi Squared Test helps us discover if one variable (Discrete X) is related to another variable (Discrete Y). This test also helps determine the level of chance between sets of data. Another name for the Chi Squared Test is the “Goodness of Fit” Statistic; which means that the test measures the level of fit between the data that is observed and the data that is projected, determined upon the variables independence. As long as the variables remain independent, the team should be able to estimate what their data trends will look like.

Here we will use the example of loan rates of two different bank branches to determine their relationship. We pose the hypothesis that there is a relationship between the two.

Null Hypothesis:
Ho = Variable A and B; Independent Variables
There is not an effect on Defaulted Loans between Branches
Alternative Hypotheses:
Ha= Variable A and B; Dependent Variables
There is an effect on Defaulted Loans between Branches

Chi Squared Test:
The Bank has 200 Loan Approvals
Branch A has 100 Loan Approvals
                5 Defaulted Loans
Branch B has 100 Loan Approvals
                9 Defaulted Loans

Question: Can we determine a “real” distinction between the two branches default rates?

Gather: Compile and summarize the visual data.
                Use this data as inputs in Minitab
                Once entered, Analyze data as a Cross Tabulation and Chi Square Test

Calculations:
R = Row total(column total/ grand total)
                Ex: 100(186/200) = 93
                All R Values will be studied to determine which will influence the relationship the most
P = 0.268
                A value less than 0.05 states there IS a relationship
                This value states that there is NOT a relationship between the branches and their default                      rates


What is your experience with the Chi Squared Test?


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