Professional Course

Intro Course: Spreadsheets and Statistics

edX, Online
4 weeks
99 USD
Next course start
Start anytime See details
Self-paced Online
4 weeks
99 USD
Next course start
Start anytime See details
Self-paced Online
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Course description

Intro Course: Spreadsheets and Statistics

Spreadsheet proficiency is a superpower. Learn how to use the various functionalities of Google Sheets to manipulate, inspect, and interpret data, separating the noise from what’s actually happening in your data set.

Upcoming start dates

1 start date available

Start anytime

  • Self-paced Online
  • Online
  • English

Who should attend?



Training content

Introduction to Spreadsheets

  • The anatomy of a spreadsheet
  • Applying basic formatting to data to improve readability
  • Manipulating data using rows, columns, and ranges
  • Using Formulas and calculations
  • Creating charts in Google Sheets and using spreadsheets to communicate insights.

Data Preparation

  • The importance of data preparation for effective data analysis
  • Importing data from different sources
  • Working with datasets in Google Sheets
  • Raw data characteristics and common issuesData cleaning
  • Using pivot tables to summarize data
  • Creating dashboards in Google Sheets

Statistics Fundamentals

  • Mean, median, and mode definitions and finding them in Google Sheets
  • Visualizing the mean in a chart
  • Identifying min, max, and range of a data set
  • Methods for inspecting data
  • Using and interpreting bar charts, line charts, and histograms

Exploratory Data Analysis

  • Identifying patterns of data distribution
  • Skew, distribution, and percentilesCalculating variance
  • Calculating standard deviation
  • Calculating z-score and interpreting it visually
  • Creating and interpreting scatterplots

Course delivery details

20-40 hours per week


  • Verified Track -$99
  • Audit Track - Free

Certification / Credits

What you'll learn

  • Master the basics of data analysis in Google Sheets with formatting, formulas, calculations, and charts.
  • Prepare data by importing from disparate sources and reducing noise with data cleaning tactics.
  • Evaluate the quality of your data and how to best use it.
  • Utilize out-of-box statistical visualizations to aid in your exploratory data analysis.

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141 Portland Street
02139 Cambridge Massachusetts


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