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Essential Statistics for Data Analysis using Excel

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About this course

This course is part of the Microsoft Professional Program Certificate in Data Science.

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 DAT205x: 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, DAT206x 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.

This course is also part of the Microsoft Excel for the Data Analyst XSeries.


  • 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

What you'll learn

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


Module 1 : Descriptive Statistics
Defining Data
Histograms and Skewness
Descriptive Statistics with Analysis ToolPak
Categorical Data, PivotTables, and PivotCharts
Summarizing Hierarchical Data
80-20 Rule and Pareto Charts
Module 1 Discussion
Module 1 Quiz
Module 1 Assessment

Module 2 : Basic Probability
Introduction to Probability
Law of Complements
Mutually Exclusive and Independent Events
Conditional Probability
Law of Total Probability and Bayes Rule
Additional Reading and Review
Module 2 Discussion
Module 2 Quiz
Module 2 Assessment

Module 3 : Random Variables
Random Variable Definitions
Mean, Variance, and Standard Deviation of a Random Variable
Mean, Variance, and Standard Deviation for Sum of Random Variables
Binomial Random Variable
Poisson Random Variable
Normal Random Variable
Central Limit Theorem
Z Scores
Module 3 Discussion
Module 3 Quiz
Module 3 Assessment

Module 4 : Sampling and Confidence Intervals
Populations and Samples
Point Estimation of a Population Mean and Proportion
The Standard Normal
Confidence Interval Estimation
Sample Size Determination
The Finite Correction Factor
Additional Reading
Module 4 Discussion
Module 4 Quiz
Module 4 Assessment

Module 5 : Hypothesis Testing
Defining Hypotheses
Type I and Type II Error
One Sample Z-Test
One Sample T-Test
Single Sample Test for Population Proportion
Testing Equality of Variances
Testing the Difference Between Two Population Means
Chi-Squared Test for Independence
Additional Reading
Module 5 Discussion
Module 5 Quiz
Module 5 Assessment

Final Exam
Post-Course Survey
Final Exam

  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    12- 24 horas en total