Introduction to Probability and Statistics in the Life Sciences

Author(s): David Vaughan

Edition: 1

Copyright: 2012

Pages: 258

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$64.83 USD

ISBN 9781465236241

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Introduction to Probability and Statistics in the Life Sciences provides a practical introduction to statistical reasoning and probability with an emphasis on applications in biology, medicine, public health, and the life sciences. The text introduces students to the fundamental concepts of probability, data analysis, statistical inference, and experimental design, equipping them with the quantitative tools needed to interpret scientific research and make evidence-based decisions.

Beginning with current problems in the life sciences, the book demonstrates how statistical thinking is essential for addressing real-world questions in genetics, ecology, epidemiology, and biomedical research. Students develop an understanding of probability theory, random variables, probability distributions, and sampling methods before progressing to estimation, confidence intervals, hypothesis testing, and descriptive statistics.

The latter chapters focus on commonly used statistical techniques, including goodness-of-fit tests, contingency table analysis, analysis of variance (ANOVA), and linear regression. These methods enable readers to analyze experimental data, evaluate relationships between variables, and draw meaningful conclusions from biological research. By integrating mathematical concepts with practical life science applications, Introduction to Probability and Statistics in the Life Sciences prepares students to confidently apply statistical methods in laboratory work, research studies, and professional practice.

CHAPTER 1: CURRENT PROBLEMS IN THE LIFE SCIENCES

CHAPTER 2: AN INTRODUCTION TO PROBABILITY

CHAPTER 3: DISTRIBUTIONS OF RANDOM VARIABLES

CHAPTER 4: SPECIAL DISCRETE RANDOM VARIABLES AND THEIR DISTRIBUTIONS

CHAPTER 5: SPECIAL CONTINUOUS RANDOM VARIABLES

CHAPTER6: PARAMETER ESTIMATION, SAMPLING DISTRIBUTIONS AND INFERENCE

CHAPTER 7: DESCRIPTIVE STATISTICS

Chapter 8: Confidence Intervals and Hypothesis Testing

Chapter 9: Goodness of Fit Tests and Contingency Tables

Chapter 10: Analysis of Variance

Chapter 11: Linear Regression

David Vaughan

Introduction to Probability and Statistics in the Life Sciences provides a practical introduction to statistical reasoning and probability with an emphasis on applications in biology, medicine, public health, and the life sciences. The text introduces students to the fundamental concepts of probability, data analysis, statistical inference, and experimental design, equipping them with the quantitative tools needed to interpret scientific research and make evidence-based decisions.

Beginning with current problems in the life sciences, the book demonstrates how statistical thinking is essential for addressing real-world questions in genetics, ecology, epidemiology, and biomedical research. Students develop an understanding of probability theory, random variables, probability distributions, and sampling methods before progressing to estimation, confidence intervals, hypothesis testing, and descriptive statistics.

The latter chapters focus on commonly used statistical techniques, including goodness-of-fit tests, contingency table analysis, analysis of variance (ANOVA), and linear regression. These methods enable readers to analyze experimental data, evaluate relationships between variables, and draw meaningful conclusions from biological research. By integrating mathematical concepts with practical life science applications, Introduction to Probability and Statistics in the Life Sciences prepares students to confidently apply statistical methods in laboratory work, research studies, and professional practice.

CHAPTER 1: CURRENT PROBLEMS IN THE LIFE SCIENCES

CHAPTER 2: AN INTRODUCTION TO PROBABILITY

CHAPTER 3: DISTRIBUTIONS OF RANDOM VARIABLES

CHAPTER 4: SPECIAL DISCRETE RANDOM VARIABLES AND THEIR DISTRIBUTIONS

CHAPTER 5: SPECIAL CONTINUOUS RANDOM VARIABLES

CHAPTER6: PARAMETER ESTIMATION, SAMPLING DISTRIBUTIONS AND INFERENCE

CHAPTER 7: DESCRIPTIVE STATISTICS

Chapter 8: Confidence Intervals and Hypothesis Testing

Chapter 9: Goodness of Fit Tests and Contingency Tables

Chapter 10: Analysis of Variance

Chapter 11: Linear Regression

David Vaughan