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Volker Bernhard Duetsch has completed

# Introduction to Statistics in Google Sheets

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4 hours
4,350 XP

## 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.

3. 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. 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.

In the following tracks

Intermediate Google Sheets

Collaborators

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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