Inferential and Descriptive Statistical Formulas in Excel

Master Excel formulas to analyze data, calculate probabilities, and perform statistical testing.

What you'll learn
- Learn to use COUNT, COUNTA, COUNTBLANK, COUNTIF, and COUNTIFS to summarize data.
- Calculate averages using AVERAGE, MEDIAN, MODE, and weighted mean formulas.
- Find extreme values using MAX, MIN, LARGE, and SMALL functions.
- Perform top and bottom "k" value calculations for focused analysis.
- Rank data and determine percentiles using Excel’s statistical tools.
- Calculate range, variance, and standard deviation to measure variability.
- Build frequency distributions to analyze data spread and groupings.
- Use formulas to extract periodic or random samples from large datasets.
- Test relationships between variables using covariance and correlation.
- Explore probability, confidence intervals, and hypothesis testing basics.

Requirements
- Microsoft Excel (Office 2021 or Microsoft 365) installed.
- Basic knowledge of Excel (e.g., entering data, simple calculations).
- Access to a computer with a stable internet connection.
- No prior advanced Excel skills required; suitable for beginners.

Description
This course focuses on building and applying statistical formulas in Microsoft Excel, with an emphasis on both descriptive and inferential analysis. It is designed for students, professionals, and data users who want to deepen their understanding of statistics and apply it using the tools built into Excel.

In the first part of the course, students will explore descriptive statistical formulas. They will learn how to count, sort, and summarize data using functions such as COUNT, COUNTIF, and COUNTIFS. The course introduces key methods for calculating averages (mean, median, and mode), as well as techniques to measure variation using range, variance, and standard deviation. Students will also discover how to analyze extremes in data using MAX, MIN, LARGE, and SMALL functions and organize information with frequency distributions.

The second part of the course covers inferential statistics. Learners will work with real-world scenarios involving sampling, probability distributions, and variable relationships. Topics include extracting random and periodic samples, calculating covariance and correlation, and interpreting probability using Excel functions. The course also introduces students to hypothesis testing and confidence intervals, preparing them to make data-driven decisions.

By the end, students will be able to perform a wide range of statistical calculations in Excel, gaining both technical skills and statistical literacy for academic, professional, or analytical tasks.

Let me know if you'd like a shorter version for a flyer or a longer one for a syllabus!

Who this course is for:
- This course is for students learning statistics using Excel.
- Ideal for business and economics majors working with real-world data.
- Great for analysts who need to summarize and interpret datasets.
- Designed for anyone performing descriptive and inferential analysis.
- Helpful for users calculating averages, ranges, and standard deviation.
- Perfect for professionals exploring data relationships and trends.
- Made for those conducting sampling and working with probability.
- Useful for Excel users applying hypothesis testing and confidence intervals.
- A fit for learners needing to build frequency distributions in Excel.
- Tailored for anyone using Excel to perform statistical calculations.
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