- Statistics for Data Science
- James D. Miller
- 150字
- 2021-07-02 14:58:51
Bringing statistics into data science
Depending on your sources and individual beliefs, you may say the following:
Statistics is data science, and data science is statistics.
To clarify this, note that there is a popular opinion that statistics might be thought of as a study or process that covers the collection, analysis, interpretation, presentation, and organization of data. As you can see, that definition is pretty similar to the data science process we described in the previous section of this chapter.
Digging deeper into this topic, one will find that statistics always involves (or a collection of) techniques or approaches used to help analyze and present data (again, this understanding could also be used to describe data science).
It is commonly accepted that the terms data science and statistics have the same meaning, at least within some circles. Again, alignment of terms and concepts is still evolving among data scientists.
推薦閱讀
- 工業(yè)機器人技術及應用
- 圖解PLC控制系統(tǒng)梯形圖和語句表
- Mastering Salesforce CRM Administration
- JMAG電機電磁仿真分析與實例解析
- Expert AWS Development
- 智能工業(yè)報警系統(tǒng)
- iClone 4.31 3D Animation Beginner's Guide
- JSF2和RichFaces4使用指南
- 自動生產線的拆裝與調試
- Storm應用實踐:實時事務處理之策略
- 水下無線傳感器網絡的通信與決策技術
- Red Hat Linux 9實務自學手冊
- Docker on Amazon Web Services
- Visual Studio 2010 (C#) Windows數(shù)據(jù)庫項目開發(fā)
- 基于ARM9的小型機器人制作