GUIDE TO ESSENTIAL BIOSTATISTICS: AGCHEM & BIOSCIENCE (THE LABCOAT GUIDE TO CROP PROTECTION Book 3)

Are you starting a new project, moving teams or starting a new role in the #cropprotection industry? The LABCOAT GUIDE TO ESSENTIAL BIOSTATISTICS is an easily accessible primer for scientists and research workers not trained in mathematical theory, and provides a readily accessible overview on how to plan, implement and analyze experiments without access to a dedicated staff of statisticians. #GuideToEssentialBiostatistics #Cropprotection #Experimentaldesign #Biostatistics #statistics
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Guide to Essential Biostatistics XIX: Linear regression (PROBIT)

In this nineteenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we cover linear dose-response curves as a method to evaluate dose response in pesticide data. #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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THE LABCOAT GUIDE TO CROP PROTECTION R&D: BOOKS I-III

THE LABCOAT GUIDE TO CROP PROTECTION R&D - the compiled version of the first three books in the LABCOAT GUIDE TO CROP PROTECTION series - is now available in eBook and Print on Amazon. Aimed at students, professionals, and others wishing to understand basic aspects of Crop Protection Development, this book is an easily accessible introduction to essential principles of Pesticide and Biopesticide Mode Of Action and Formulation, Biostatistics as well as Strategic R&D Management for Pesticide & BioPesticide R&D. By purchasing the print edition of this book, you are eligible for a FREE download of the eBook version, providing access to high-resolution, zoomable color images. #sustainability #bioscience #cropprotection #resources#consulting #agrochemicals #biologicalcontrol#marketingstrategy #researchdevelopment #consultation#formulation #businessdevelopment
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CROP PROTECTION R&D - independent resources

Are you interested in the development of sustainable Crop Protection solutions? The LABCOAT GUIDE TO CROP PROTECTION is an easily accessible introduction to essential principles of Pesticide and Biopesticide Mode Of Action and Formulation, Strategic R&D Management and Basic BioStatistics! #sustainability #bioscience #cropprotection #resources #consulting #agrochemicals #biologicalcontrol #marketingstrategy #researchdevelopment #consultation #blueoceanstrategy #businessdevelopment
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Guide to Essential Biostatistics XVII: Inferential Statistics - post ANOVA tests

In this seventeenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we cover ANOVA tests. While the t-test is used to compare the means of two treatments, samples or groups, Analysis of Variance (ANOVA) are hypothesis tests used to differentiate between the means of more than two treatments, or groups. The most common application of ANOVA in crop protection R&D is the one-way ANOVA, used to differentiate between the means of more than two treatments, for which there is one measurement variable (e.g. plant height) and one nominal variable, or factor (e.g. pesticide). #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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Guide to Essential Biostatistics XVI: Inferential Statistics - ANOVA

In this sixteenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we cover ANOVA tests. While the t-test is used to compare the means of two treatments, samples or groups, Analysis of Variance (ANOVA) are hypothesis tests used to differentiate between the means of more than two treatments, or groups. The most common application of ANOVA in crop protection R&D is the one-way ANOVA, used to differentiate between the means of more than two treatments, for which there is one measurement variable (e.g. plant height) and one nominal variable, or factor (e.g. pesticide). #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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Guide to Essential Biostatistics XV: Inferential Statistics - Two Sample Means Comparison: the t-Test (Part II)

In this fifteenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we cover the t-test (part II). For biological experiments, the objective of most trials is to determine whether the means of the measured variables are equal (the null hypothesis) or whether they are significantly different. The t-tests are a group of inferential parametric methods used to determine if two samples (or a sample and a theoretical mean) have the same mean (null hypothesis), or if there is a significant difference between the means. #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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Guide to Essential Biostatistics XIV: Inferential Statistics - Two Sample Means Comparison: the f-Test

In this fourteenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we cover the f-test. The (unpaired) two-sample t-test assumes that the data is sampled from populations that have equal variances, even if their means are different. As part of the (unpaired) two-sample t-test analysis, the f-test is used to test if two samples have equal variances. The f-test computes the ratio of the larger (greater) sample variance (square of the standard deviation, SD) relative to the smaller (lesser) variance. #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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THE LABCOAT GUIDE TO CROP PROTECTION R&D: BOOKS I-III

Are you starting a new project, moving teams or starting a new role in the #cropprotection industry? The LABCOAT GUIDE TO CROP PROTECTION aims to give you a complete introduction to Pesticide and Biopesticide Mode Of Action and Formulation, Strategic R&D Management and Essential BioStatistics! THE LABCOAT GUIDE TO CROP PROTECTION R&D - the compiled version of the first three books in the LABCOAT GUIDE TO CROP PROTECTION series - is now available in eBook and Print on Amazon. By purchasing the print edition of this book, you are eligible for a FREE download of the eBook version, providing access to high-resolution, zoomable color images.
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Guide to Essential Biostatistics XIII: Inferential Statistics - Two Sample Means Comparison: the t-Test (Part I)

In this thirteenth article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we introduce the t-test. For biological experiments, the objective of most trials is to determine whether the means of the measured variables are equal (the null hypothesis) or whether they are significantly different. The t-tests are a group of inferential parametric methods used to determine if two samples (or a sample and a theoretical mean) have the same mean (null hypothesis), or if there is a significant difference between the means. #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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