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Wednesday, December 5 Chi-square Test of Independence: Two Variables. Summing up!

Wednesday, December 5 Chi-square Test of Independence: Two Variables. Summing up!. Chi-square Test of Independence. Are two nominal level variables related or independent from each other?. Is race related to SES, or are they independent?. White. Black. 15. Hi. SES. 32. Lo. 47. 28.

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Wednesday, December 5 Chi-square Test of Independence: Two Variables. Summing up!

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  1. Wednesday, December 5 Chi-square Test of Independence: Two Variables. Summing up!

  2. Chi-square Test of Independence Are two nominal level variables related or independent from each other? Is race related to SES, or are they independent?

  3. White Black 15 Hi SES 32 Lo 47 28 19

  4. Row n x Column n Total n The expected frequency of any given cell is (15x28)/47 (15x19)/47 15 8.94 6.06 (32x28)/47 (32x19)/47 32 19.06 12.94 47 28 19

  5. White Black 12 15 Hi 3 SES 32 Lo 16 16 47 28 19

  6. r c 2 (fo - fe)2   = fe c=1 r=1 Please calculate: 12 3 15 8.94 6.06 16 16 32 19.06 12.94 47 28 19

  7. Bivariate Statistics Y Nominal Ordinal Interval Nominal2 Rank-sum t-test Kruskal-Wallis H ANOVA Ordinal Spearman rs (rho) Interval Pearson r Regression X

  8. Who said this? "The definition of insanity is doing the same thing over and over again and expecting different results".

  9. Who said this? I hate this quote! "The definition of insanity is doing the same thing over and over again and expecting different results". I hate this quote! I hate this quote! I hate this quote! I hate this quote!

  10. I don’t like it because from a statistical point of view, it is insane to do the same thing over and over again and expect the same results! • More to the point, the wisdom of statistics lies in understanding that repeating things some ways ends up with results that are more the same than others. Hmm. Think about this for a moment. Statistics allows one to understand the expected variability in results even when the same thing is done, as a function of σ and N.

  11. Your turn! • If I take a sample of N=1, why can’t I make inferences to the larger population from this sample?

  12. Your turn! • If I take a sample of N=1, why can’t I make inferences to the larger population from this sample? What does Guinness have to do with it?

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