Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL Server 2016 Developer's Guide

You're reading from   SQL Server 2016 Developer's Guide Build efficient database applications for your organization with SQL Server 2016

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786465344
Length 616 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to SQL Server 2016 FREE CHAPTER 2. Review of SQL Server Features for Developers 3. SQL Server Tools 4. Transact-SQL Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening the Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2016 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R in SQL Server

Intermediate statistics - associations

In the previous chapter, you learned about the discrete statistics methods for getting the information about the distribution of discrete and continuous variables. In a data science project, the next typical step is to check for the associations between pairs of variables.

When checking for the associations between pairs of variables, you have three possibilities:

  • Both variables are discrete
  • Both variables are continuous
  • One discrete and one continuous variable

Besides dealing with two variables only, this section also introduces linear regression, one of the most important statistical methods, where you model a single response (or dependent) variable with a regression formula that includes one or more predictor (or independent) variables.

Altogether, you will learn about the following in this section:

  • Chi-squared test of independence of two discrete variables
  • Phi coefficient, contingency coefficient, and Cramer's V coefficient that measures the association...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime