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- https://bio.libretexts.org/Bookshelves/Introductory_and_General_Biology/Biology_(Kimball)/20%3A_General_ScienceThis page discusses the need for controlled experiments to establish causation between factors A and B, highlighting the impracticalities in human studies that lead to the use of epidemiological metho...This page discusses the need for controlled experiments to establish causation between factors A and B, highlighting the impracticalities in human studies that lead to the use of epidemiological methods. It emphasizes the importance of validating new drugs and treatments through clinical studies to ensure they improve upon existing methods. Additionally, it outlines the scientific approach, which combines common sense with specific characteristics that define scientific inquiry.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.13%3A_Multiple_RegressionThis 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.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Genetics_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_New_Page/1.13%3A_Simulation_ModelingThis page discusses quantitative genetic models and their relevance in plant breeding, highlighting the historical debate between Fisher and Wright on model complexity. It addresses the practical appl...This page discusses quantitative genetic models and their relevance in plant breeding, highlighting the historical debate between Fisher and Wright on model complexity. It addresses the practical application of simulation modeling using Excel to analyze genetic contributions, including SNP genotypes and phenotypic traits.
