Course Objective

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?
Course Outline

### 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
• Regression
• When to use it
• How to interpret meaningfully
• For nonlinear data
• Exponential Regression
• Logarithmic Regression
• Polynomial Regression
• ANOVA
• Chi-Square
• Time Series & Forecasting
• Logistic Regression Overview Duration 2 to 4
Materials

Manual and supporting materials included

Prerequisites

Students should be familiar with writing calculations and formulas within Excel

Software Requirements