Table of Contents

• 1: Do those shoes fit?
• 2: Dilbert's 3 day work week
• 3: The day is saved ... or not
• 4: What you observe vs expect
• 5: The Chi-squared Equation
• 6: Give it a try
• Detour
• 7: What's a p-value?
• 8: What's a Lookup Table?
• 9: What's a "df"?
• Completing the Chi-squared Test
• 10: Interpreting a chi-squared
• 11: The answer, finally
• 12: Summary
• 13: What about 90% M/F sick days?
• 14: What about 50% M/F sick days?
• Chi-squared in Biology
• 15: Testing for a dihybrid ratio
• 16: Review and Words of Wisdom

The answer, finally

So, we have a chi-squared value that we calculated, called chi-squared statistic (0.167) and a chi-squared value that we looked up, called the chi-squared critical value (3.84). Comparing these two values, we find that our chi-squared statistic is much smaller than the chi-squared critical value (0.167 < 3.84), which means the deviations were small and the model fits the data.

This supports Dilbert's hypothesis that sick days were random.

So employees are probably really sick and not out fishing on those Mondays and Fridays.