蔡澜寻味世界系列 寻味中国 大食会
- 作者蔡澜著
- 出版社青岛：青岛出版社
- 标注页数279 页
- 文件页数289 页
- 文件大小33.77 MB
- 出版时间2018
- ISBN9787555267737
The art of data analysis how to answer almost any question using basic statisticsKristin H. Jarman · Wiley · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || IndexJarman, Kristin H. · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || GlossaryJarman, Kristin H. · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || ReferencesJarman, Kristin H. · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || Statistics: The Life of the PartyJarman, Kristin H. · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || Asteroid Belts and Spandex Cars: Using Descriptive Statistics to Answer Your Most Weighty QuestionsJarman, Kristin H. · 2013
The Art of Data Analysis (How to Answer Almost Any Question Using Basic Statistics) || Appendix A: Critical Values for the Standard Normal DistributionJarman, Kristin H. · 2013
Applications and Challenges of Forensic ProteomicsMerkley, Eric D.; Wunschel, David S.; Wahl, Karen L.; Jarman, Kristin H. · Forensic Science International · 2019
A new approach to automated peak detectionKristin H. Jarman; Don S. Daly; Kevin K. Anderson; Karen L. Wahl · 2003
Beyond Basic Statistics (Tips, Tricks, and Techniques Every Data Analyst Should Know) ||Jarman, Kristin H. · 2015
Beyond Basic Statistics (Tips, Tricks, and Techniques Every Data Analyst Should Know) || GlossaryJarman, Kristin H. · 2015
Beyond Basic Statistics (Tips, Tricks, and Techniques Every Data Analyst Should Know) || IndexJarman, Kristin H. · 2015
Beyond Basic Statistics (Tips, Tricks, and Techniques Every Data Analyst Should Know) || IntroductionJarman, Kristin H. · 2015
The art of data analysis how to answer almost any question using basic statisticsKristin H. Jarman · Wiley · 2013
Beyond Basic Statistics (Tips, Tricks, and Techniques Every Data Analyst Should Know) || Front MatterJarman, Kristin H. · 2015