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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.

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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.

This course is ideal for anyone interested in building their professional toolkit and growing their career with hard skills such as:

  • Understanding the anatomy of a spreadsheet
  • Using formulas to automate manual processes
  • The ability to work with data sets in Google Sheets
  • Knowing which data matters when answering a business question
  • Identifying the level of importance to assign to your results

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What's inside

Learning objectives

  • 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.

Syllabus

Introduction to Spreadsheets
The anatomy of a spreadsheet
Applying basic formatting to data to improve readability
Manipulating data using rows, columns, and ranges
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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

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Geared toward professionals and students seeking career growth through data analysis in the workplace
Covers fundamental spreadsheet concepts, making it accessible to learners with varying levels of experience
Emphasizes practical applications of spreadsheet skills, focusing on real-world data analysis scenarios
Taught by instructors with expertise in data analysis and spreadsheet applications
Lacks hands-on projects or interactive exercises that reinforce learning
May require additional resources for learners with no prior experience in spreadsheets

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro Course: Spreadsheets and Statistics with these activities:
Revisit your data analysis skills
Sharpen your skills with data manipulation and analysis, which are essential for mastering the various formulas in Google Sheets.
Show steps
  • Review your notes or textbooks on data manipulation and analysis
  • Practice manipulating and analyzing data in a spreadsheet using a sample dataset
Review basic spreadsheet concepts
Reinforce fundamental concepts of spreadsheets, ensuring a solid foundation for exploring advanced topics in Google Sheets.
Show steps
  • Review the anatomy of a spreadsheet
  • Practice manipulating data using rows, columns, and ranges
  • Refresh knowledge on basic formulas and calculations
Follow tutorials on using pivot tables in Google Sheets
Utilize online tutorials to gain a deeper understanding of pivot tables in Google Sheets, empowering data summarization and analysis.
Show steps
  • Search for reputable tutorials on using pivot tables in Google Sheets
  • Follow the tutorials and practice creating pivot tables
  • Experiment with different pivot table settings and options
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice formatting data in Google Sheets
Practice applying different formatting options to data in Google Sheets to improve readability and organization.
Show steps
  • Explore the formatting options in the Format menu
  • Apply formatting to different data types (e.g., numbers, dates, currency)
  • Experiment with conditional formatting to highlight specific values
Join a Google Sheets study group
Engage with fellow learners to grasp concepts, exchange knowledge, and assist each other in resolving challenges within Google Sheets.
Show steps
  • Connect with other students through online forums or social media groups dedicated to Google Sheets
  • Participate in discussions, ask questions, and share your insights
Collaborate on a Google Sheets project with a peer
Work with a classmate to complete a project in Google Sheets, fostering collaboration and knowledge sharing while improving problem-solving skills.
Show steps
  • Find a peer who is also taking the course
  • Choose a project to work on together
  • Divide the work and collaborate on the project
  • Present the completed project to the class
Attend a workshop on advanced Google Sheets formulas
Attend a hands-on workshop to learn advanced formula techniques in Google Sheets, enabling more efficient data analysis and manipulation.
Show steps
  • Research and identify a reputable workshop on advanced formulas
  • Register for the workshop and attend the scheduled sessions
  • Participate actively in the workshop and take notes on key concepts
Create a dashboard to visualize Google Sheets data
Develop a dashboard that presents key insights and trends from data in Google Sheets, allowing for easy data visualization and interpretation.
Show steps
  • Identify the key metrics and insights to be displayed on the dashboard
  • Choose appropriate chart and visualization types
  • Create and format the dashboard using Google Sheets tools
Develop a data analysis tool using Google Sheets
Create a custom tool in Google Sheets to automate data analysis tasks, enhancing efficiency and providing a personalized solution for specific data manipulation needs.
Show steps
  • Identify a problem or task that can be automated in Google Sheets
  • Design the tool and develop the necessary formulas and scripts
  • Test the tool and iterate on the design
  • Document the tool for ease of use and sharing

Career center

Learners who complete Intro Course: Spreadsheets and Statistics will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst collects, processes, and analyzes data using statistical and data analysis techniques. This course teaches the basics of data analysis using real-world examples in Google Sheets. You will be able to use your newfound knowledge of spreadsheets, formulas, and visualizations to help you import data, clean and manipulate it, and use it to answer important business questions.
Statistician
A Statistician collects, analyzes, and interprets data to draw conclusions and make predictions. This course teaches the fundamentals of statistics, including how to calculate mean, median, mode, and standard deviation. These concepts are commonly used by Statisticians to summarize and analyze data.
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment recommendations. This course teaches the basics of data analysis and statistics, which are commonly used by Quantitative Analysts. By completing this course, you will be able to build a foundation in data analysis and prepare for a career as a Quantitative Analyst.
Market Research Analyst
A Market Research Analyst collects, analyzes, and interprets market data to identify trends and make recommendations for businesses. This course teaches the basics of data analysis, including how to import, clean, and visualize data. These skills will be helpful for Market Research Analysts who need to understand and interpret market data.
Operations Research Analyst
An Operations Research Analyst uses advanced analytical techniques to solve complex business problems. This course can help build a foundation in data analysis, statistics, and visualization techniques that are commonly used in Operations Research. With this knowledge, you will be able to model and solve problems, and improve the efficiency of operations.
Business Analyst
A Business Analyst gathers and analyzes data to improve business processes and make informed decisions. This course can help build a foundation in data analysis and visualization techniques that can be used to analyze business data. By understanding how to identify patterns and trends in data, Business Analysts can make recommendations for improvements or changes to business processes.
Data Scientist
A Data Scientist uses statistical and machine learning techniques to extract insights from data. This course teaches the basics of data analysis and visualization, which are commonly used by Data Scientists to explore and understand data. By completing this course, you will be able to build a foundation in data analysis and prepare for a career as a Data Scientist.
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations and assess the financial health of companies. This course teaches the basics of data analysis, including how to import, clean, and visualize data. These skills are commonly used by Financial Analysts when analyzing financial data.
Epidemiologist
An Epidemiologist investigates the causes of disease and other health problems. This course teaches the fundamentals of statistics, including how to calculate mean, median, mode, and standard deviation. These concepts are commonly used by Epidemiologists to analyze health data.
Actuary
An Actuary analyzes financial data to assess risk and make recommendations for insurance policies. This course teaches the fundamentals of statistics, including how to calculate mean, median, mode, and standard deviation. These concepts are commonly used by Actuaries to analyze risk and make recommendations.
Data Engineer
A Data Engineer designs and builds systems for storing and processing data. This course teaches the basics of data analysis, including how to clean and prepare data. These skills are commonly used by Data Engineers to prepare data for analysis.
Information Systems Manager
An Information Systems Manager plans and manages information technology systems. This course teaches the basics of data analysis using Google Sheets, which can be useful for Information Systems Managers who need to analyze data to make informed decisions about IT systems. By completing this course, you will be able to build a foundation in spreadsheet programming and data visualization.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course teaches the basics of data analysis using Google Sheets, which can be useful for Software Engineers who need to analyze data to improve the performance of their applications. By completing this course, you will be able to build a foundation in spreadsheet programming and data visualization.
Database Administrator
A Database Administrator designs and manages databases. This course teaches the basics of data analysis and data visualization, which can be useful for Database Administrators who need to analyze data to improve the performance of their databases. By completing this course, you will be able to build a foundation in data analysis and spreadsheet programming.
Project Manager
A Project Manager plans and manages projects. This course teaches the basics of data analysis and visualization, which can be useful for Project Managers who need to analyze data to track project progress and make informed decisions. By completing this course, you will be able to build a foundation in data analysis and spreadsheet programming.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Intro Course: Spreadsheets and Statistics.
An introduction to data science concepts, providing a broad overview of the field and its applications in business.
A comprehensive textbook covering core statistical concepts and their applications in business and economics.
A comprehensive guide to data science using Python, covering essential tools and techniques.
A hands-on guide to deep learning using the Keras library in Python, suitable for learners with programming experience.

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