24小时热门版块排行榜

>论坛更新日志 (2806)
>虫友互识 (330)
>文献求助 (178)
>硕博家园 (146)
>导师招生 (118)
>论文投稿 (83)
>休闲灌水 (68)
>招聘信息布告栏 (55)
>考博 (55)
>基金申请 (50)
>博后之家 (49)
>教师之家 (49)
>金融投资 (42)
>考研 (30)
>找工作 (29)
>论文道贺祈福 (24)

返回列表

【奖励】本帖被评价12次，作者zjx121610增加金币 10.5 个

当前主题已经存档。

zjx121610

木虫 (文坛精英)

应助: 0 (幼儿园)
贵宾: 0.35
金币: 3551.1
帖子: 10774
在线: 16.6小时
虫号: 205726

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

当您的朋友需要提取此文件时只需: 匿名提取文件连接 http://pickup.mofile.com/7899083760164850 或登录Mofile，使用提取码 7899083760164850 提取文件

(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

回复此楼