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?
About Six Sigma Development Solutions, Inc.
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