Lean Six Sigma with Python — Chi-Squared Test

Perform a Chi-Squared Test to explain a shortage of drivers impacting your transportation network

Lean Six Sigma with Python — Chi-Squared Test for Driver Allocation Problem
Solve a Driver Allocation Problem with Chi-Squared Test — (Image by Author)
SUMMARY
I. Problem Statement
Transportation delays are due to drivers' allocation issues?
II. Data Analysis
1. Exploratory Data Analysis

Analysis with Python sample data from historical records
2. Perform Cross Tabulation
Summarise the relationship between several categorical variables.
3. Pearson’s Chi-Square Test
Validate that your results are significant and not due to random fluctuation
III. Conclusion

I. Problem Statement

1. Scenario

Driver Allocation Problem with Chi-Squared Test using Python
Driver Allocation Problem with Chi-Squared Test using Python
Replenishment order process from the request of the factory to driver allocation — (Image by Author)

II. Data Analysis

1. Exploratory Data Analysis

Stacked Bart Charts — (Image by Author)

2. Perform Cross Tabulation

Split of shipments by HUB for each driver
Split of shipments (%) per Driver for each HUB
Split of shipments (%) per HUB for each Driver
Minitab
Menu Stats> Tables > Cross Tabulation and Chi-Square

3. Pearson’s Chi-Squared Test

p-value is 0.410

III. Conclusion

References

Senior Supply Chain Engineer — http://samirsaci.com | Data Science for Warehousing📦, Transportation 🚚 and Demand Forecasting 📈