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[资源] （Oxford 05）Data Analysis for Chemistry！

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(Oxford 05)Data Analysis for Chemistry

ISBN: 0195162110
Title: Data Analysis for Chemistry:
An Introductory Guide for Students and Laboratory Scientists
Author: D. Brynn Hibbert J. Justin Gooding
Publisher: Oxford University Press, USA
Publication Date: 2005-10-27
Number Of Pages: 192
2.2 Mb pdf

Chemical data analysis, with aspects of metrology in chemistry and chemometrics, is an evolving discipline where new and better ways of doing things are constantly being developed. This book makes data analysis simple by demystifying the language and whenever possible giving unambiguous ways of doing things. Based on author D. Brynn Hibberts lectures on data analysis to undergraduates and graduate students, Data Analysis for Chemistry covers topics including measurements, means and confidence ..

Contents
Readers’ Guide: Definitions, Questions, and Useful Functions:
Where to Find Things and What to Do 1
1. Introduction 21
1.1. What This Chapter Should Teach You 21
1.2. Measurement 21
1.3. Why Measure? 21
1.4. Definitions 22
1.5. Calibration and Traceability 23
1.6. So Why Do We Need to Do Data Analysis at All? 23
1.7. Three Types of Error 24
1.8. Accuracy and Precision 31
1.9. Significant Figures 35
1.10. Fit for Purpose 37
2. Describing Data: Means and Confidence Intervals 39
2.1. What This Chapter Should Teach You 39
2.2. The Analytical Result 39
2.3. Population and Sample 40
2.4. Mean, Variance, and Standard Deviation 41
2.5. So How Do I Quote My Uncertainty? 49
2.6. Robust Estimators 61
2.7. Repeatability and Reproducibility of Measurements 64
3. Hypothesis Testing 67
3.1. What This Chapter Should Teach You 67
3.2. Why Perform Hypothesis Tests? 67
3.3. Levels of Confidence and Significance 68
3.4. How to Test If Your Data Are Normally Distributed 72
3.5. Test for an Outlier 77
3.6. Determining Significant Systematic Error 82
3.7. Testing Variances: Are Two Variances Equivalent? 87
3.8. Testing Two Means (Means t-Test) 90
3.9. Paired t-Test 94
3.10. Hypothesis Testing in Excel 97
4. Analysis of Variance 99
4.1. What This Chapter Should Teach You 99
4.2. What Is Analysis of Variance (ANOVA)? 99
4.3. Jargon 101
4.4. One-Way ANOVA 101
4.5. Least Significant Difference 105
4.6. ANOVA in Excel 106
4.7. Sampling 112
4.8. Multiway ANOVA 115
4.9. Two-Way ANOVA in Excel 116
4.10. Calculations of Multiway ANOVA 125
4.11. Variances in Multiway ANOVA 125
5. Calibration 127
5.1. What This Chapter Should Teach You 127
5.2. Introduction 127
5.3. Linear Calibration Models 129
5.4. Calibration in Excel 147
5.5. r2: A Much Abused Statistic 153
5.6. The Well-Tempered Calibration 154
5.7. Standard Addition 155
5.8. Limits of Detection and Determination 160
Appendix 165
Bibliography 169
Index 173

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