Serves as a primer for all chemists who
Statistics in Spectroscopy, Second Edition, is an expanded and updated version of the original title. The aim of the book is to bridge the gap between the average chemist/spectroscopist and the study of statistics.
The book introduces the novice reader to the ideas and concepts of statistics and uses spectroscopic examples to show how these concepts are applied. Several key statistical concepts are introduced through the use of computer programs.
All spectroscopists and those involved in statistics and analysis of data, both chemical and biological, especially those in chemistry, statistics, computer science and biology departments. Also relevant to the manufacturing, pharmaceutical, agricultural and textile industries, and all large corporations with analytical chemistry and chemical engineering departments.
Statistics in Spectroscopy, 2nd Edition
Chapter 1 Introduction: Why this Book?
Chapter 2 Important Concepts from Probability Theory
Chapter 3 Populations and Samples: The Meaning of "Statistics"
Chapter 4 Degrees of Freedom
Chapter 5 Introduction to Distributors and Probability Sampling
Chapter 6 The Normal Distribution
Chapter 7 Alternative Ways to Calculate Standard Deviation
Chapter 8 The Central Limit Theorem
Chapter 9 Synthesis of Variance
Chapter 10 Where are we and Where are we Going?
Chapter 11 More and Different Statistics
Chapter 12 The T Statistic
Chapter 13 Distribution of Means
Chapter 14 One-and Two-Tailed Tests
Chapter 15 Philosophical Interlude
Chapter 16 Biased and Unbiased Estimators
Chapter 17 The Variance of Variance
Chapter 18 Hypothesis Testing of Chi-Square
Chapter 19 More Hypothesis Testing
Chapter 20 Statistical Inferences
Chapter 21 How to Count
Chapter 22 And Still Counting
Chapter 23 Contingency Tables
Chapter 24 What do you Mean: Random?
Chapter 25 The F Statistics
Chapter 26 Precision and Accuracy: Introduction to Analysis of Variance
Chapter 27 Analysis of Variance and Statistical Design of Experiments
Chapter 28 Crossed and Nested Experiments
Chapter 29 Miscellaneous Considerations Regarding Analysis of Variance
Chapter 30 Pitfalls of Statistic
Chapter 31 Pitfalls of Statistic Continued
Chapter 32 Calibration in Spectroscopy
Chapter 33 Calibration: Linear Regression as a Statistical Technique
Chapter 34 Calibration: Error Sources in Calibration
Chapter 35 Calibration: Selecting the Calibration Samples
Chapter 36 Calibration: Developing the Calibration Model
Chapter 37 Calibration: Auxiliary Statistics for the Calibration Model
Chapter 38 The Beginning