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HomeProbability & StatisticsIntroduction to Statistics in Google Sheets

Introduction to Statistics in Google Sheets

4.3+
13 reviews
Beginner

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

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4 Hours15 Videos51 Exercises
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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 Google Sheets 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!

Comprehensive Curriculum

This course offers a comprehensive curriculum covering the fundamental aspects of statistical analysis. You'll start with the basics of data collection and move on to exploring different types of data and their properties. We'll delve into descriptive statistics, teaching you how to summarize and interpret data using measures like mean, median, and mode. You'll also learn about probability and its role in statistics, including concepts such as probability distributions and expected values.

Practical Application and Case Studies

One of the unique aspects of this course is the emphasis on practical application. You'll not only learn the theory behind statistical methods but also how to apply them in real-world scenarios using Google Sheets. This hands-on approach is further enhanced by a series of case studies. These case studies, using diverse datasets such as eBay auctions, train ridership, and historical presidential approval ratings, will provide you with the opportunity to apply your knowledge and skills in analyzing and interpreting real data. By the end of the course, you'll be able to conduct your own analyses and draw meaningful conclusions from data sets in various contexts.

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  1. 1

    Getting To Know Your Data

    Free

    Begin 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.

    Play Chapter Now
    Welcome to the course!
    50 xp
    Don't be average!
    100 xp
    Presidential approval rating averages
    100 xp
    Difference between median and mean
    100 xp
    Modal madness
    100 xp
    How far from average?
    50 xp
    Train variation
    100 xp
    Calculating standard deviations
    100 xp
    Playing quarters
    100 xp
    Standardizing data
    50 xp
    Comparing z-scores
    100 xp
    Exploring eBay auctions
    100 xp
  2. 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 Google Sheets using statistical plots such as the histogram, scatter plot, and bar plot.

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In the following tracks

Intermediate Google Sheets

Collaborators

Collaborator's avatar
Chester Ismay
Collaborator's avatar
Yashas Roy
Ted Kwartler HeadshotTed 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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*4.3
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  • Natthawit J.
    10 months

    Good for beginner learning

  • Albert F.
    over 1 year

    It is a complex subject that requires more than one reading and understanding.

  • Jonathan V.
    over 1 year

    I love it! Very clear and too easy to understand.

  • Kamil M.
    over 1 year

    I love how easy it is to learn with DataCamp. Great content and plenty of paths and courses to choose from. Thanks Guys!

  • Hugo P.
    over 1 year

    Good course. The exercises were great!

"Good for beginner learning"

Natthawit J.

"It is a complex subject that requires more than one reading and understanding."

Albert F.

"I love it! Very clear and too easy to understand."

Jonathan V.

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