Introduction to Statistics in Spreadsheets
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
- 4 hours
- 15 Videos
- 51 Exercises
- 4,895 Participants
- 4,350 XP
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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!
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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.
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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.
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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.
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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.
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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.
-
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.
-
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.
-
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.
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Lloyd's Banking Group
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Decision Science Analytics @ USAA
Ted Kwartler
Senior Director, Data Scientist at Liberty Mutual
Ted started his text mining journey at Amazon when he launched the social media customer service team. Since then, he has held analytical leadership roles at startups and Fortune 100 companies. He is the Author of "Text Mining in Practice with R" available at Amazon.
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Collaborators
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Chester Ismay
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Yashas Roy