So, Chi Square is going to be a statistical test, so we're about to get into a lot of math. I'm really sorry, but it's genetics it has an application in it. So the Chi Square Test is a statistical test, and what it is testing for is whether the expected result that you get is very similar to the observed result. So the expected is what you expected to get and the observed is what you actually see. So the reason we have to have this test is because in genetics, it's never perfect. Right? You, I mean, if you mate organisms together and you get, you know, 2000 offspring, for instance, or flies or something, you're not going to get a perfect 3 to 1 ratio. You're just not. Because there's 2000 offspring. It may be very close, but it's not going to be perfect. I mean, it's just not - life has never worked that way. You also won't get the perfect 9 to 3 to 3 to 1 ratio either. Life isn't perfect. Genetics isn't perfect. And so, if we are doing this experiment, say, we have a bunch of flies, we have 6000 flies, and we counted them all. We have these nice ratios, and it's like, really, it's like 2.96 to 1. You know, is that actually close enough to 3 to 1 to say, okay, this is our normal, this is so close to expected, this is Mendelian inheritance. So that's what the Chi Square Test is for. So it's used to check if your numbers that you got from your experiment are close enough to be expected to say that, to say that, you know, it's Mendelian inheritance. So the important numbers that you have to know to do a Chi Square Analysis are the observed numbers. These are the numbers you actually get in your experiment. And the expected numbers, and these are the numbers that you are expected to get. The perfect ratio, the 3 to 1, the perfect Punnett Square, that is the expected. And so, of course, because we're doing math, there's going to be a formula and it looks like this. Realize it's kind of confusing. Here's your Chi Square, that's what it looks like, that's the notation for it. You don't remember from math, this means sum. And then you have these o's and e's. So what do those stand for? Well, o very clearly means observed number, so these are the numbers you get. And the expected numbers, use green, are the numbers that you, the perfect ratio numbers. So, that's an overview. Let's now move on to the actual practice question and practice using Chi Square, and an actual question that you might get. So let's move on.
χ 2 = ∑ i ( o i - e i ) 2 / e iTable of contents
- 1. Introduction to Genetics51m
- 2. Mendel's Laws of Inheritance3h 37m
- 3. Extensions to Mendelian Inheritance2h 41m
- 4. Genetic Mapping and Linkage2h 28m
- 5. Genetics of Bacteria and Viruses1h 21m
- 6. Chromosomal Variation1h 48m
- 7. DNA and Chromosome Structure56m
- 8. DNA Replication1h 10m
- 9. Mitosis and Meiosis1h 34m
- 10. Transcription1h 0m
- 11. Translation58m
- 12. Gene Regulation in Prokaryotes1h 19m
- 13. Gene Regulation in Eukaryotes44m
- 14. Genetic Control of Development44m
- 15. Genomes and Genomics1h 50m
- 16. Transposable Elements47m
- 17. Mutation, Repair, and Recombination1h 6m
- 18. Molecular Genetic Tools19m
- 19. Cancer Genetics29m
- 20. Quantitative Genetics1h 26m
- 21. Population Genetics50m
- 22. Evolutionary Genetics29m
3. Extensions to Mendelian Inheritance
Chi Square Analysis
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