Course Outline
Module 1: Introduction to The Course
· Introduction to Analytics
· Different Types of Analytics
· Why are There So Many Different Methods?
· Terminology and Notation
· Core Ideas in Data Analytics
· The Steps in Data Analytics Projects
Module 2: Data Exploration
· Introduction to Statistics
· Variable Types
· Summarizing Data
· Descriptive Statistics: Measures of Central Tendency
· Descriptive Statistics: Measures of Variation
· Statistical Displays: Histograms and Boxplots
Module 3: Excel for Data Analysis
· Introduction to Excel
· Sort/Filter/Conditional Formatting
· Pivot Tables
· Data Visualization
Module 4: Breakeven Analysis
• Linear Functions
• Revenue and Cost Models
• Exponential Functions
• Curve Fitting
• What-If Analysis / Goal Seek
Module 5: Time Value of Money
• Basics of lending and borrowing
• Interest
• Present and future value of investments
• Simple Interest
• Compound Interest
Module 6: Probability Models
· Basic Principles
· Conditional Probability
· Discrete Random Variables
· Continuous Random Variables
· Normal Distribution
· Z-score
· Outlier Detection Method
Module 7: Statistical Inferences
· Sampling Types / Survey Errors
· Confidence Intervals
· t-Distribution
· Introduction to Hypothesis Testing
· Single Sample t-Test
· Type I/II Errors
Module 8: Linear Regression – Part 1
· Supervised vs. Unsupervised Methods
· Explanatory vs. Predictive Modeling
· Correlation
· Simple Linear Regression
· Dealing with Categorical Variable in Regression
· Multiple Linear Regression
· Fit Measures
Exercises and Software:
- Within each module, students will be provided with lots of in-class hands on exercises to practice the materials on their own and/or with the guidance of the instructor.
- Class materials, including lecture notes and exercises will be provided to students.