Search
- Filter Results
- Location
- Classification
- Include attachments
- https://bio.libretexts.org/Bookshelves/Genetics/Classical_Genetics_(Khan_Academy)/01%3A_Introduction_to_heredity/1.10%3A_Practice_-_Punnett_squares_and_probabilityOffspring that have at least one R and S allele must be rude and sneaky because the allele for rude (R) is dominant to the allele for respectful (r) and the allele for sneaky (S) is dominant to the al...Offspring that have at least one R and S allele must be rude and sneaky because the allele for rude (R) is dominant to the allele for respectful (r) and the allele for sneaky (S) is dominant to the allele for sincere (s). The father is homozygous recessive (bb), so he can only give the recessive b allele to the offspring, while the mother is homozygous dominant (BB), so she can only give the dominant B allele to the offspring.
- https://bio.libretexts.org/Bookshelves/Genetics/Classical_Genetics_(Khan_Academy)/01%3A_Introduction_to_heredity/1.07%3A_Probabilities_in_geneticsThe sum rule and product rule. Applying these rules to solve genetics problems involving many genes.
- https://bio.libretexts.org/Bookshelves/Introductory_and_General_Biology/Biology_(Kimball)/20%3A_General_Science/20.05%3A_Statistical_MethodsThis page discusses how biologists manage numerical data by comparing discrete and continuous variables. It covers relevant calculations such as mean, standard deviation, and standard error of the mea...This page discusses how biologists manage numerical data by comparing discrete and continuous variables. It covers relevant calculations such as mean, standard deviation, and standard error of the mean (S.E.M.) to evaluate data reliability. Confidence limits are highlighted for assessing the probable range of a population's true mean, typically at a 95% confidence level.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.02%3A_Distributions_and_ProbabilityThis page covers the scientific method and experimental design principles, emphasizing the importance of proper sampling and data representation. It explains data visualization with histograms, introd...This page covers the scientific method and experimental design principles, emphasizing the importance of proper sampling and data representation. It explains data visualization with histograms, introduces statistical concepts such as quartiles, and discusses probability measures and distributions. The normal distribution is highlighted for its properties and use in probability calculations, including Z-scores.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_ChaptersThis page covers fundamental statistical concepts and methods, including distributions, the central limit theorem, hypothesis testing, and categorical data analysis. It discusses continuous data, line...This page covers fundamental statistical concepts and methods, including distributions, the central limit theorem, hypothesis testing, and categorical data analysis. It discusses continuous data, linear correlation, regression techniques, ANOVA, and data transformation methods. Advanced topics include multiple and nonlinear regression as well as multivariate analysis, complemented by algebra review and applied learning activities.
- https://bio.libretexts.org/Workbench/Modern_Genetics/01%3A_What_is_a_gene/1.04%3A_Probabilities_in_geneticsThe sum rule and product rule. Applying these rules to solve genetics problems involving many genes.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.03%3A_Central_Limit_Theorem_Confidence_Intervals_and_Hypothesis_TestsThis page covers statistical concepts including normal distribution, Central Limit Theorem, confidence intervals, and hypothesis testing. It illustrates how sample means from normal and non-normal dis...This page covers statistical concepts including normal distribution, Central Limit Theorem, confidence intervals, and hypothesis testing. It illustrates how sample means from normal and non-normal distributions behave, emphasizing reduced variance with increased sample size. Methods for evaluating normality using temperature data and calculating z-scores with Excel are discussed.
