Essential Statistics for Data Analysis using Excel

Gain a solid understanding of statistics and basic probability, using Excel, and build on your data analysis and data science foundation.
  • Self-Paced Learning

    Learning Style
  • Intermediate

    Difficulty
  • 24 Hours

    Course Duration
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Gain a solid understanding of statistics and basic probability, using Excel, and build on your data analysis and data science foundation.

About this course

If you’re considering a career as a data analyst, you need to know about histograms, Pareto charts, Boxplots, Bayes’ theorem, and much more. In this applied statistics course, the second in our Microsoft Excel Data Analyst XSeries, use the powerful tools built into Excel, and explore the core principles of statistics and basic probability—from both the conceptual and applied perspectives. Learn about descriptive statistics, basic probability, random variables, sampling and confidence intervals, and hypothesis testing. And see how to apply these concepts and principles using the environment, functions, and visualizations of Excel.

As a data science pro, the ability to analyze data helps you to make better decisions, and a solid foundation in statistics and basic probability helps you to better understand your data. Using real-world concepts applicable to many industries, including medical, business, sports, insurance, and much more, learn from leading experts why Excel is one of the top tools for data analysis and how its built-in features make Excel a great way to learn essential skills.

Before taking this course, you should be familiar with organizing and summarizing data using Excel analytic tools, such as tables, pivot tables, and pivot charts. You should also be comfortable (or willing to try) creating complex formulas and visualizations. Want to start with the basics? Check out Introduction to Data Analysis using Excel. As you learn these concepts and get more experience with this powerful tool that can be extremely helpful in your journey as a data analyst or data scientist, you may want to also take the third course in our series, Analyzing and Visualizing Data with Excel

This course includes excerpts from Microsoft Excel 2016: Data Analysis and Business Modeling from Microsoft Press and authored by course instructor Wayne Winston.

Course Objective:

  • Descriptive statistics
  • Basic probability
  • Random variables
  • Sampling and confidence intervals
  • Hypothesis testing

Audience:

  • Data Scientists

Prerequisites:

  • Secondary school (high school) algebra
  • Ability to work with tables, formulas, and charts in Excel
  • Ability to organize and summarize data using Excel analytic tools such as tables, pivot tables, and pivot charts
  • Excel 2016 is required for the full course experience. Excel 2013 will work but will not support all the visualizations and functions.
More Information
Brand Microsoft
Lab Access No
Technology Microsoft
Learning Style Self-Paced Learning
Difficulty Intermediate
Course Duration 24 Hours
Language English
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