Table 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
3:29 minutes
Problem 28b
Textbook Question
Textbook QuestionTo assess Mendel's law of segregation using tomatoes, a true-breeding tall variety (SS) is crossed with a true-breeding short variety (ss). The heterozygous F₁ tall plants (Ss) were crossed to produce two sets of F₂ data, as follows. Set I Set II _ 30 tall 300 tall 5 short 50 short Using the X² test, analyze the results for both datasets. Calculate X² values and estimate the p values in both cases.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Mendel's Law of Segregation
Mendel's Law of Segregation states that during the formation of gametes, the two alleles for a trait separate, so that each gamete carries only one allele for each gene. This principle explains how offspring inherit one allele from each parent, leading to the observed ratios in phenotypes. In the context of the tomato cross, this law helps predict the expected ratios of tall and short plants in the F₂ generation.
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Chi-Square Test (X² Test)
The Chi-Square Test is a statistical method used to determine if there is a significant difference between observed and expected frequencies in categorical data. In genetics, it helps assess whether the observed ratios of phenotypes align with the expected ratios based on Mendelian inheritance. By calculating the X² value, researchers can evaluate the fit of their data to the expected genetic model.
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P-Value
The p-value is a statistical measure that helps determine the significance of results obtained from a hypothesis test. It indicates the probability of observing the data, or something more extreme, if the null hypothesis is true. In the context of the Chi-Square Test, a low p-value (typically less than 0.05) suggests that the observed data significantly deviates from the expected ratios, leading to the rejection of the null hypothesis.
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