Excel Statistics for Business Analytics
Published by O'Reilly Media, Inc.
Explore, visualize, and make inferences about data using spreadsheets
Inferential statistics involves inferring parameters of a population based on the values of a sample. Professionals in ecommerce, manufacturing, and other industries use inferential statistics as the basis for decision making.
Join expert George Mount for a hands-on approach to conducting statistical inference, conducted in Microsoft Excel. By the end of this course, users will be able to organize, present, and draw valid conclusions from data, using inferential statistics for business impact.
What you’ll learn and how you can apply it
By the end of this live online course, you’ll understand:
- What variables are, and how to explore them given their type
- How the central limit theorem provides the “missing link” between descriptive and inferential statistics
- The roles statistics and visualizations each play in effective quantitative analysis
And you’ll be able to:
- Explore a dataset for potential research questions, check assumptions, and build hypotheses
- Test formally whether the value of one group is greater than another, on average, given their respective samples
- Make compelling business recommendations using inferential statistics
This live event is for you because...
- You want to apply more rigorous methods to your business decision making.
- You’re an Excel user interested in learning more about data science.
- You’re a researcher or analyst looking to apply statistical methods to business.
Prerequisites
- A computer with the Excel Data Analysis ToolPak loaded (instructions)
- Intermediate Excel skills (relative and absolute cell references, PivotTables, building bar and line charts, etc.)
- No previous statistical knowledge required
Recommended preparation:
- Read “Evaluating Data in the Real World” and “Understanding Excel’s Statistical Capabilities” (chapters 1 and 2 in Statistical Analysis with Excel for Dummies, fourth edition)
Recommended follow-up:
- Read Advancing into Analytics (book)
- Read Statistical Analysis: Microsoft Excel 2016 (book)
- Read Data Smart: Using Data Science to Transform Information into Insight (book)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Exploratory data analysis in Excel (50 minutes)
- Presentation: What is a variable, and how do you measure it?; different types of variables, both quantitative and qualitative; how they’re used in business analytics; looking at a variable with visualizations; using histograms and box plots to paint a picture of a variable’s distribution; listening to a variable with descriptive statistics; using measures of central tendency and dispersion to explore the data statistically
- Hands-on exercise: Identify and visualize variables in a real-world business dataset
- Q&A
Break (10 minutes)
Foundations of inferential statistics (60 minutes)
- Presentation: Intro to the Data Analysis ToolPak; loading and exploring the free Office plug-in for various statistical analyses; the central limit theorem—saved by the bell curve; demonstrating the central limit theorem’s role in providing valid inferences about a population, given a sample; What is a hypothesis, and how do you test it?; intro to hypothesis testing in statistical analysis; how to craft one; What is a t-test, and when do you use it?; the use case for an independent samples t-test; how to check for the necessary assumptions and preprocess the data
- Hands-on exercise: Inspect and prepare a dataset to test
- Q&A
Break (10 minutes)
T-tests for business impact (50 minutes)
- Presentation: Evaluating for substantive and statistical significance; analyzing the p-value and confidence interval to make informed and well-rounded business decisions; presenting the results for management buy-in; preparing recommendations and visualizations to present before a general business audience
- Hands-on exercises: Conduct a t-test using the Data Analysis ToolPak; visualize a t-test’s results
- Q&A
Your Instructor
George Mount
George Mount is the founder and CEO of Stringfest Analytics, a consulting firm specializing in analytics education and upskilling. He has worked with leading bootcamps, learning platforms and practice organizations to help individuals excel at analytics.
George regularly blogs and speaks on data analysis, data education and workforce development and is the author of Advancing into Analytics: From Excel to Python and R (O'Reilly Media, 2021) and _Modern Data Analytics in Excel: Using Power Query, Power Pivot and More for Enhanced Data Analytics _(O'Reilly Media, 2024). He is a recipient of the Microsoft Most Valuable Professional (MVP) award for exceptional technical expertise and community advocacy in the field of Excel.
George holds a bachelor’s degree in economics from Hillsdale College and master’s degrees in finance and information systems from Case Western Reserve University. He resides in Cleveland, Ohio.