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Statistics and Scientific Method An Introduction for Students and Researchers 1st Edition by Peter J Diggle, Amanda G Chetwynd ISBN 0199543186 9780199543182

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Statistics and Scientific Method An Introduction for Students and Researchers 1st Edition Peter J. Diggle Digital Instant Download

Author(s): Peter J. Diggle, Amanda G. Chetwynd
ISBN(s): 9780199543182, 0199543186
Edition: 1
File Details: PDF, 4.63 MB
Year: 2011
Language: english
SKU: EB-5546766 Category: Tags: ,

Statistics and Scientific Method An Introduction for Students and Researchers 1st Edition by Peter J Diggle, Amanda G Chetwynd – Ebook PDF Instant Download/Delivery: 0199543186, 9780199543182
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ISBN 10: 0199543186
ISBN 13: 9780199543182
Author: Peter J Diggle, Amanda G Chetwynd

Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended audience of non-mathematically inclined undergraduate or postgraduate students, typically in a single discipline; hence, “statistics for biologists”, “statistics for psychologists”, and so on.

An antidote to technique-oriented service courses, Statistics and Scientific Method is different. It studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, the text aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling and data analysis are integral to the scientific method.

Aimed primarily at beginning postgraduate students across a range of scientific disciplines (albeit with a bias towards the biological, environmental and health sciences), it therefore assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation.

Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice, R, whilst the book’s web-page includes downloadable data and R code that enables the reader to reproduce all of the analyses in the book and, with easy modifications, to adapt the code to analyse their own data if they wish. However, the book is not intended to be a textbook on statistical computing, and all of the material in the book can be understood without using either R or any other computer software.

Statistics and Scientific Method An Introduction for Students and Researchers 1st Table of contents:

Chapter 1: Introduction to the Scientific Method

  • What is Science?

  • The Role of Observation and Experimentation

  • Hypotheses, Theories, and Laws

  • The Cycle of Scientific Inquiry

Chapter 2: Basics of Statistical Thinking

  • Understanding Variability

  • Descriptive vs. Inferential Statistics

  • Types of Data: Qualitative and Quantitative

  • Scales of Measurement

Chapter 3: Data Collection and Experimental Design

  • Sampling Methods

  • Designing Experiments and Studies

  • Controlling Variables and Bias

  • Randomization and Replication

Chapter 4: Descriptive Statistics

  • Measures of Central Tendency (Mean, Median, Mode)

  • Measures of Dispersion (Range, Variance, Standard Deviation)

  • Graphical Representations of Data (Histograms, Boxplots, Scatterplots)

Chapter 5: Probability Fundamentals

  • Basic Probability Concepts

  • Probability Distributions

  • The Law of Large Numbers

  • Conditional Probability and Independence

Chapter 6: Statistical Inference

  • Sampling Distributions

  • Point Estimation and Confidence Intervals

  • Hypothesis Testing Fundamentals

  • Errors in Hypothesis Testing (Type I and Type II)

Chapter 7: Comparing Groups and Relationships

  • t-Tests and ANOVA

  • Correlation and Regression Analysis

  • Nonparametric Tests

Chapter 8: Designing Robust Research

  • Ethical Considerations in Research

  • Reporting Statistical Results

  • Reproducibility and Replicability

  • Common Pitfalls and Misinterpretations

Chapter 9: Advanced Topics (Optional/For Further Study)

  • Bayesian Statistics

  • Multivariate Analysis

  • Power Analysis and Sample Size Determination

  • Meta-analysis

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Tags: Peter J Diggle, Amanda G Chetwynd, Statistics, Scientific, Researchers