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Introduction to Statistics

This article will give a brief overview of how statistics are generated, stored, and used in SQL Server.  Read more...
By Johnny Bieber 2017/10/17 | Source: SQLServerCentral.com | Category: statistics
Rating: |  Discuss |   Briefcase | 1,428 reads

Statistics in SQL: Student’s t-test

Many undergraduates have misunderstood the name 'Students' in the t-test to imply that it was designed as a simple test suitable for students. In fact it was William Sealy Gosset, an Englishman publishing under the pseudonym Student, who developed the t-test and t distribution in 1908, as a way of making confident predictions from small sample sizes of normally-distributed variables. As Gosset's employer was Guinness, the brewer, Phil Factor takes a sober view of calculating it in SQL.  Read more...
By Additional Articles 2017/10/12 | Source: SimpleTalk | Category: statistics
Rating: (not yet rated)  Rate this |   Briefcase | 3,478 reads

Pattern Recognition via Principal Components Analysis

We'll look at using principal components analysis to help visualise your data and detect underlying structure or patterns.  Read more...
By Nick Burns 2017/09/12 | Source: SQLServerCentral.com | Category: r language
Rating: |  Discuss |   Briefcase | 808 reads

Statistics in SQL: The Mann–Whitney U test

Phil Factor shows how to use the Mann-Whitney U test in SQL to to find out whether two samples come from the same distribution.  Read more...
By Additional Articles 2017/09/04 | Source: SimpleTalk | Category: t-sql
Rating:  Rate this |   Briefcase | 3,801 reads

Statistics in SQL: The Kruskal–Wallis Test

Before you report your conclusions about your data, have you checked whether your 'actionable' figures occurred by chance? The Kruskal-Wallis test is a safe way of determining whether samples come from the same population, because it is simple and doesn't rely on a normal distribution in the population. This allows you a measure of confidence that your results are 'significant'. Phil Factor explains how to do it.  Read more...
By Additional Articles 2017/07/27 | Source: SimpleTalk | Category: t-sql
Rating:  Rate this |   Briefcase | 5,336 reads

Machine Learning for Outlier Detection in R

A look into clustering to detect outliers in R. An extension on univariate statistical tests to include multivariate data.  Read more...
By Nick Burns 2017/07/05 | Source: SQLServerCentral.com | Category: r language
Rating: |  Discuss |   Briefcase | 669 reads

Scoring Outliers in Non-Normal Data with R

Using R to detect outliers is relatively easy, but most methods assume your data is normally distributed. How do you handle skewed datasets?  Read more...
By Nick Burns 2017/06/29 | Source: SQLServerCentral.com | Category: outlier detection
Rating: |  Discuss |   Briefcase | 606 reads

Statistics in SQL: Simple Linear Regressions

Although linear regressions can get complicated, most jobs involving the plotting of a trendline are easy. Simple Linear Regression is handy for the SQL Programmer in making a prediction of a linear trend and giving a figure for the level probability for the prediction, and what is more, they are easy to do with the aggregation that is built into SQL.  Read more...
By Additional Articles 2017/06/22 | Source: SimpleTalk | Category: statistics
Rating: (not yet rated)  Rate this |   Briefcase | 4,674 reads

Statistics in SQL: Kendall’s Tau rank correlation

Statistical calculations in SQL are often perfectly easy to do. SQL was designed to be a natural fit for calculating correlation, regression and variance on large quantities of data. It just isn't always immediately obvious how. In the second of a series of articles, Phil factor shows how calculating a non-parametric correlation via Kendall's Tau or Spearman's Rho can be stress-free.  Read more...
By Additional Articles 2017/06/20 | Source: SimpleTalk | Category: statistics
Rating: (not yet rated)  Rate this |   Briefcase | 3,178 reads

Scoring Outliers with R

What is normal? More to the point, what is abnormal? We will look at using R to score outliers in a typical monitoring dataset.  Read more...
By Nick Burns 2017/06/19 | Source: SQLServerCentral.com | Category: r language
Rating: |  Discuss |   Briefcase | 839 reads

What is normal? Finding outliers with R

How do you currently set alerting thresholds? What is normal? And more importantly, what is truly abnormal? We will explore these questions.  Read more...
By Nick Burns 2017/06/13 | Source: SQLServerCentral.com | Category: r language
Rating: |  Discuss |   Briefcase | 993 reads

Statistics in SQL: Pearson’s Correlation

Some people will assure you that you can't do any serious statistical calculations in SQL. In the first of a series of articles, Phil factor aims to prove them wrong by explaining how easy it is to calculate Pearson's Product Moment Correlation.  Read more...
By Additional Articles 2017/06/09 | Source: SimpleTalk | Category: statistics
Rating:  Rate this |   Briefcase | 4,419 reads

Can I Use Statistics to Design Indexes?

"I’ve noticed that many indexes in my data warehouse aren’t used frequently. Is there a way to use the automatically generated statistics to make useful indexes?" Kendra Little answers the question in episode 18 of Dear SQL DBA.  Read more...
By Additional Articles 2016/11/15 | Category: statistics
Rating:  Rate this |   Briefcase | 4,439 reads

Introduction to Microsoft R Services in SQL Server 2016

General introduction to R Services in SQL Server 2016 and how R server works with external stored procedure.  Read more...
By Tomaž Kaštrun 2016/09/15 | Source: SQLServerCentral.com | Category: microsoft
Rating: |  Discuss |   Briefcase | 3,231 reads
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