Students will leave the course able to use Excel to build statistical models that answer questions like:
- What’s the relationship between a variable and an outcome?
- If I adjust X, what will be the impact on Y? Are there natural limits I should be aware of?
- Are we meeting expectations?
- What’s coming next? Are we going up or down and by how much?
- Why are we going up or down? How impactful is each variable? (in other words, what should I focus on first?)
- Are there any unusual outliers? What caused those? Do I need to do something about this?
- How likely is any given idea or decision or campaign to be successful?
- Did any given change or decision make a material business impact?
Section I: Background Information
- Why use statistics?
- Installing the Data Analysis Tool Pack add-in for Excel
Section II: Analysis Fundamentals
- Exploring and visualizing data
- Descriptive Statistics
- Uses for Specific Measures and how to visualize
- Samples vs. populations
- Average, median, standard deviation, quartiles, percentiles, z-scores
- Looking at the shape of the data and the impact of outliers
- Cautions and common pitfalls (e.g. Anscombe’s Quartet)
- Examining Relationships
- Overview of Probability
- Sampling Distributions and the Central Limit Theorem
- Overview of Inference
- Confidence intervals and p-values
Section III: Predictive Models
- Method for Creating Predictive Models
- How to Choose and Assess an Appropriate Model
- When to use it
- How to interpret meaningfully
- For nonlinear data
- Exponential Regression
- Logarithmic Regression
- Polynomial Regression
- Time Series & Forecasting
- Logistic Regression Overview
Manual and supporting materials included
Students should be familiar with writing calculations and formulas within Excel
Access to Microsoft Excel