SQL for Statistics Essential Training
49mIntermediate2018-03-09
Authors
Dan Sullivan
Enterprise Architect, Big Data Expert
Course details
Descriptive statistics help us understand the overall structure of data, and SQL is the most widely used language for manipulating it. Together, they can help data analysts derive better insights and make far-reaching predictions. This course provides an overview of basic descriptive statistics and the SQL commands you need to know to summarize data sets, find averages, and calculate variance and standard deviation. Instructor Dan Sullivan also introduces more detailed analysis techniques using discreet and continuous percentiles to help segment data, and correlations between variables to identify relationships. He concludes with an introduction to linear regression, a widely used predictive analytics technique.
Learning objectives
Define variance and standard deviation.
Calculate discrete percentiles.
Calculate continuous percentiles.
Analyze correlations.
Explore linear models, such as linear regression.
Learning objectives
Define variance and standard deviation.
Calculate discrete percentiles.
Calculate continuous percentiles.
Analyze correlations.
Explore linear models, such as linear regression.
Skills covered
PostgreSQLDatabase AdministrationDatabase DevelopmentDatabase ManagementData AnalysisEssential TrainingProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware Development
Concepts
0. Introduction
- 01 - Welcome
- 02 - What you should know
- 03 - Exercise files
1. Basic Descriptive Statistics
- 04 - Installing PostgreSQL
- 05 - Load data into PostgreSQL
- 06 - Basics - Count, minimum, and maximum
- 07 - Basics - Sum and average
- 08 - Variance and standard deviation
2. Percentiles and Frequencies
- 09 - Introduction to percentiles
- 10 - Discrete percentiles
- 11 - Continuous percentiles
- 12 - Summary of percentiles
3. Correlations and Ranks
- 13 - Introduction to correlation
- 14 - Correlations between variables
- 15 - ROW NUMBER
- 16 - Mode
- 17 - Summary of correlations
4. Linear Models
- 18 - Introduction to linear regression
- 19 - Minimizing error
- 20 - Computing intercept
- 21 - Computing slope
Conclusion
- 22 - Overview of SQL for statistics
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