Table of Contents

• 1: Do those shoes fit?
• 2: The 3-day work week
• 3: The day is saved ... or not
• 4: What you observe vs. expect
• 5: The Chi-Square 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-Square Test
• 10: Interpreting a chi-square
• 11: The answer, finally
• 12: Summary
• 13: What about 90% M/F sickdays?
• 14: What about 50% M/F sickdays?
• Chi-Square in Biology
• 15: Testing for a dihybrid ratio
• 16: Review and Words of Wisdom

Detour stop #2: what's a Lookup Table?

So, so far we have a chi-square-calc, which has a p-value associated with it. This would be fine and dandy IF we actually knew what that p-value was. But we don't. And in fact, finding out the p-value for any given chi-square-calc would involve a complicated mathematical formula. Believe it or not, biologists are not actually big on complicated mathematical formulas (or formuli either). So instead we have a lookup table. Or as I like to say, a Magic Lookup Table, because for our purposes, it might as well have appeared magically.

What the lookup table tells you is, for your specific dataset, what the chi-square calc is that would correspond with p=0.05. This special number is called the "chi-square-crit", as in the critical value or threshold value of the chi-square-calc.

 

And how do you know that this chi-square-crit is the one and only chi-square-crit that fits your exact dataset? It turns out that you only need to know one thing about your dataset, which is how many rows are in the chi-square table. If your chi-square table has 2 rows (like ours), then you look up the chi-square crit under df = 1 (cuz 2-1 = 1, more about that on the next page).