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About 29 results
  • 1.5: Categorical Data Multivariate
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.05%3A_Categorical_Data_Multivariate
    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...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.
  • Quantitative Methods for Plant Breeding (Suza and Lamkey)
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)
    This open textbook covers common statistics used in agriculture research, including experimental design in plant breeding and genetics, as well as the analysis of variance, regression, and correlation...This open textbook covers common statistics used in agriculture research, including experimental design in plant breeding and genetics, as well as the analysis of variance, regression, and correlation.
  • InfoPage
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/00%3A_Front_Matter/02%3A_InfoPage
    This page describes the LibreTexts Project, which offers free, customizable open educational resources to reduce textbook costs. Instructors can adopt and remix materials tailored to their courses wit...This page describes the LibreTexts Project, which offers free, customizable open educational resources to reduce textbook costs. Instructors can adopt and remix materials tailored to their courses within a platform supported by educational bodies and the National Science Foundation. It features 14 interconnected libraries catering to various educational needs, and users can reach out for more information or connect via social media.
  • About the PBEA Series
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/00%3A_Front_Matter/05%3A_About_the_PBEA_Series
    This page discusses the Plant Breeding E-Learning in Africa (PBEA) e-modules, developed through a collaboration between Iowa State University and several African universities, funded by the Bill & Mel...This page discusses the Plant Breeding E-Learning in Africa (PBEA) e-modules, developed through a collaboration between Iowa State University and several African universities, funded by the Bill & Melinda Gates Foundation. Aimed at educating students on crop breeding management, the modules address real-world cultivar development challenges and include Applied Learning Activities.
  • Table of Contents
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/00%3A_Front_Matter/03%3A_Table_of_Contents
  • Index
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/zz%3A_Back_Matter/10%3A_Index
  • 1.13: Multiple Regression
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.13%3A_Multiple_Regression
    This page covers multiple regression analysis, detailing its application in agricultural yield studies based on various independent variables like fertilizer, water, nitrogen, and drought. Key topics ...This page covers multiple regression analysis, detailing its application in agricultural yield studies based on various independent variables like fertilizer, water, nitrogen, and drought. Key topics include correlation calculations, significance testing, polynomial regression, and model fitting using R software. The analyses aim to understand and predict yield variations while addressing challenges like multicollinearity and heteroscedasticity.
  • 1.4: Categorical Data - Binary
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.04%3A_Categorical_Data_-_Binary
    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, 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.
  • 1.7: Linear Correlation, Regression and Prediction
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.07%3A_Linear_Correlation_Regression_and_Prediction
    This page explores the relationship between continuous variables through correlation and regression analysis, including the use of Pearson Correlation Coefficient and scatter plots for visualization. ...This page explores the relationship between continuous variables through correlation and regression analysis, including the use of Pearson Correlation Coefficient and scatter plots for visualization. It discusses methods to create regression lines, interpret coefficients, and assess statistical significance through techniques like ANOVA and F-tests. The importance of recognizing variability, calculating confidence limits, and addressing outliers is emphasized.
  • 1.15: Multivariate Analysis
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.15%3A_Multivariate_Analysis
    This page covers multivariate data analysis, emphasizing grouping, variable interactions, similarity measures, and dataset simplification using R. It discusses dissimilarity coefficients for categoric...This page covers multivariate data analysis, emphasizing grouping, variable interactions, similarity measures, and dataset simplification using R. It discusses dissimilarity coefficients for categorical and quantitative data, data cleaning for statistical analysis, and clustering methods like k-means and hierarchical clustering. Principal Component Analysis (PCA) is highlighted for dimensionality reduction, with over 96% variance explained by three components.
  • Contributors
    https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/00%3A_Front_Matter/06%3A_Contributors
    This page highlights the contributions of Walter Suza and Kendall Lamkey at Iowa State University, emphasizing Suza's role in plant breeding education in Africa and Lamkey's focus on corn breeding and...This page highlights the contributions of Walter Suza and Kendall Lamkey at Iowa State University, emphasizing Suza's role in plant breeding education in Africa and Lamkey's focus on corn breeding and quantitative genetics as the Associate Dean for Facilities and Operations. The chapter also mentions various other authors and contributors in the field of plant sciences.

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