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- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.05%3A_Categorical_Data_MultivariateThis page covers the use of multinomial distributions and Chi-square (χ2) tests for analyzing categorical data. It explains procedures for testing genetic ratio hypotheses (such as 3:1 and 9:3...This page covers the use of multinomial distributions and Chi-square (χ2) tests for analyzing categorical data. It explains procedures for testing genetic ratio hypotheses (such as 3:1 and 9:3:3:1), assessing independence and homogeneity, and using contingency tables. The text highlights practical applications, significance in plant studies, and calculations of chi-square statistics, including Yates’ Correction for small samples.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.04%3A_Categorical_Data_-_BinaryThis page covers concepts related to binomial data, focusing on scenarios with two possible outcomes, such as success or failure. It introduces binomial distribution, calculations for probabilities, m...This page covers concepts related to binomial data, focusing on scenarios with two possible outcomes, such as success or failure. It introduces binomial distribution, calculations for probabilities, means, variances, and confidence intervals, emphasizing sample size and independence. Applications include estimating the number of trials needed and using normal approximation for large samples. Key statistical methods discussed involve hypothesis testing and comparing proportions.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.01%3A_Basic_PrinciplesThis page emphasizes the critical role of experimentation in agricultural research, particularly in seed science and plant breeding, outlining the scientific method and the importance of replication, ...This page emphasizes the critical role of experimentation in agricultural research, particularly in seed science and plant breeding, outlining the scientific method and the importance of replication, randomization, and controlled design to enhance data accuracy. It discusses statistical measures for analyzing crop data, proper reporting of measurements, and the significance of using consistent units.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.08%3A_The_Analysis_of_Variance_(ANOVA)This page introduces ANOVA for comparing multiple treatments, emphasizing its advantages over the t-test. It covers constructing ANOVA tables, calculating sums and mean squares, and determining the F-...This page introduces ANOVA for comparing multiple treatments, emphasizing its advantages over the t-test. It covers constructing ANOVA tables, calculating sums and mean squares, and determining the F-ratio for significance testing, along with a focus on corn yield examples. Critical F-values are provided for statistical reference.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.10%3A_Mean_ComparisonsThis page covers various statistical methods, mainly ANOVA, for comparing treatment means in agricultural experiments, particularly with corn varieties and planting densities. It highlights calculatio...This page covers various statistical methods, mainly ANOVA, for comparing treatment means in agricultural experiments, particularly with corn varieties and planting densities. It highlights calculations of Least Significant Difference (LSD) and Honestly Significant Difference (HSD), emphasizing their relevance, differences, and application while minimizing Type I errors. Contrasts are discussed for hypothesis testing in yielding differences, integrating computational tools.
- https://bio.libretexts.org/Bookshelves/Evolutionary_Developmental_Biology/Phylogenetic_Comparative_Methods_(Harmon)/02%3A_Fitting_Statistical_Models_to_Data/2.02%3A_Standard_Statistical_Hypothesis_TestingStandard hypothesis testing approaches focus almost entirely on rejecting null hypotheses. In the framework (usually referred to as the frequentist approach to statistics) one first defines a null hyp...Standard hypothesis testing approaches focus almost entirely on rejecting null hypotheses. In the framework (usually referred to as the frequentist approach to statistics) one first defines a null hypothesis. This null hypothesis represents your expectation if some pattern, such as a difference among groups, is not present, or if some process of interest were not occurring.
- 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.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.06%3A_Continuous_DataThis page covers statistical methods for hypothesis testing in agricultural research, focusing on sample means from normal distributions, t-tests for comparing treatment means, and confidence interval...This page covers statistical methods for hypothesis testing in agricultural research, focusing on sample means from normal distributions, t-tests for comparing treatment means, and confidence intervals, emphasizing practical calculation through Excel. It details approaches like the paired and independent t-tests, as well as the Least Significant Difference (LSD) method for evaluating mean differences.
- https://bio.libretexts.org/Courses/Monterey_Peninsula_College/Raskoff_Environmental_Science/01%3A_Intro_to_Environmental_Science/1.05%3A_The_Process_of_ScienceThis page explores environmental science, emphasizing its integration of biology, chemistry, and geology through the scientific method, which involves observation, hypothesis formulation, and experime...This page explores environmental science, emphasizing its integration of biology, chemistry, and geology through the scientific method, which involves observation, hypothesis formulation, and experimentation. It discusses an experiment on phosphate's effect on algal growth, distinguishing between basic science—aimed at knowledge for its own sake—and applied science, which addresses real-world challenges.
