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

Play it again, Sam!

What if 90% of the sick days were on Monday or Friday?

	observed ("o")	expected ("e")	(o-e)	(o-e)2	(o-e)2/e
Monday or Friday
Midweek
Total	100	100
Check

 

degrees of freedom	Χ2 crit for α = 0.055
1	3.84
2	5.99
3	7.81
4	9.49
5	11.07
6	12.59
7	14.07
8	15.51
9	16.92
10	18.31

Ok, so now take that calculated chi-squared value and compare it to the critical chi square value on the table.

 

 

You should have got a chi-squared statistic of 104.166, compared to the chi-squared critical value of 3.84. The chi-squared statistic is much greater than the chi-squared critical value-- so the data does not fit the model and you reject your null hypothesis. In other words, Dilbert's random sick day model does NOT hold up.