Introduction to Statistics in Spreadsheets
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
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Course Description
Statistics is the science that deals with the collection, analysis, and interpretation of data. Having a solid foundation in statistics will help you effectively work with your data to test hypotheses and uncover insights that can help solve your problems. This course is designed to give you that foundation in statistics. Using Spreadsheets functions, you'll dive into averages, distributions, hypothesis testing, and conclude the course by applying your newfound knowledge in a case study. Along the way, you'll work with a variety of datasets ranging from eBay auctions to train ridership to historical presidential approval ratings. Enjoy!
- 1
Getting To Know Your Data
FreeBegin your journey by learning why and how to summarize your data using statistics such as the mean, median, and mode. While working with a variety of datasets ranging from Amazon revenue to U.S Presidential ratings, you'll learn about the differences between each of these fundamental statistics and most importantly, when to use each. - 2
Statistical Data Visualization
Data visualization is one of the most important parts of any data science workflow. It leads to a deeper understanding of your dataset which in turn allows you to more effectively communicate results to stakeholders. In this chapter, you'll learn how to visualize your data in Spreadsheets using statistical plots such as the histogram, scatter plot, and bar plot. - 3
Statistical Hypothesis Testing
This chapter introduces you to statistical hypothesis testing. You'll learn how to construct a hypothesis, test it using different statistical tests, and properly interpret the results. - 4
Case Study: Dating Profile Analysis
The final stretch! Apply all of your newfound statistical knowledge and solidify everything you have learned by working through a case study consisting of online dating profile data.
Yashas Roy
Chester IsmayPrerequisites
Data Analysis in Spreadsheets
Ted Kwartler
Adjunct Professor, Harvard University
Ted Kwartler is the VP, Trusted AI at DataRobot. At DataRobot, Ted sets product strategy for explainable and ethical uses of data technology in the company's application. Ted brings unique insights and experience utilizing data, business acumen and ethics to his current and previous positions at Liberty Mutual Insurance and Amazon. In addition to having 4 DataCamp courses he teaches graduate courses at the Harvard Extension School and is the author of Text Mining in Practice with R.
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Decision Science Analytics, USAA
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