Course overview
In this course, you’ll learn several techniques for sampling data, such as random sampling and cluster sampling. You’ll also learn about discrete variables and random variables in the context of frequency distributions, and the different types of charts and graphs you might use to visualize frequency distributions.
As you learn about these concepts and how to use them for more robust data analysis, you’ll be working with a dataset about basketball players in the WNBA (Women’s National Basketball Association) that contains general information about players, along with their metrics for the 2016-2017 season.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. At the end of the course, you’ll complete a portfolio project that asks you to investigate Fandango Movie Ratings to determine if Fandango is inflating movie ratings on its site. This is an opportunity to learn to identify and overcome common setbacks in practical data analysis.
Key skills
- Sampling data using simple, random sampling, stratified sampling, and cluster sampling
- Employing and measuring variables in statistics
- Building, visualizing, and comparing frequency distribution tables
Course outline
Summarizing Data in SQL [4 lessons]
Summary Statistics with SQL 1h
Lesson Objectives- Combine aggregate functions with the WHERE clause
- Combine aggregate and scalar functions
- Combine aggregate functions and arithmetic operators
Group Summary Statistics with SQL 1h
Lesson Objectives- Define the GROUP BY clause
- Apply the GROUP BY clause
- Employ the GROUP BY clause with aggregate functions
Multiple Group Summary Statistics 1h
Lesson Objectives- Group database rows based on several criteria
- Filter aggregate rows
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Build confidence with our in-depth projects, and show off your data skills.
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Work with real data from day one with interactive lessons and hands-on exercises.
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