Easy Statistics for Food Science with R
eBook - ePub

Easy Statistics for Food Science with R

  1. 228 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Easy Statistics for Food Science with R

About this book

Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs.This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data.- Contains numerous step-by-step tutorials help the reader to learn quickly- Covers the theory and application of the statistical techniques- Shows how to analyze data using R software- Provides R scripts for all examples and figures

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Yes, you can access Easy Statistics for Food Science with R by Abbas F.M. Alkarkhi,Wasin A. A. Alqaraghuli in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Food Science. We have over one million books available in our catalogue for you to explore.
Chapter 1

Introduction

Abstract

This chapter is an introductory chapter to answer questions regarding multivariate analysis, including the nature of the data, how to organize multivariate data to be ready for analysis, and how to apply multivariate analysis. Furthermore, the difference between univariate statistical methods that address a single variable and multivariate methods that address several responses is given both to clarify the picture for the reader and to demonstrate the importance of using multivariate analysis. The organization of multivariate data is described in an easy way to enable novices to understand the nature of such data. Moreover, a normal distribution for both cases (univariate and multivariate) is given with the density functions. In addition, a variety of real case studies from the field of food science for multivariate models are given to show the organization of the data to the reader in a simple ...

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Preface
  7. Chapter 1. Introduction
  8. Chapter 2. Introduction to R
  9. Chapter 3. Statistical Concepts
  10. Chapter 4. Measures of Location and Dispersion
  11. Chapter 5. Hypothesis Testing
  12. Chapter 6. Comparing Several Population Means
  13. Chapter 7. Regression Models
  14. Chapter 8. Principal Components Analysis
  15. Chapter 9. Factor Analysis
  16. Chapter 10. Discriminant Analysis and Classification
  17. Chapter 11. Cluster Analysis
  18. Appendix
  19. Index