Build a strong foundation in data analytics by exploring both descriptive and inferential statistics, and learn how data drives forecasting and strategic decisions in various industries. Dive into statistical modeling and analysis, covering essential algorithms, theorems, and real-world applications.
Overview
Syllabus
Basic Data Analysis
- Measures of Central Tendency
- Measures of Position
- Measures of Dispersion
- The Normal Curve
- Descriptive Statistics
Predictive Analytics I
- Forecasting
- Series Forecast
Data Visualization I
- Charts
- Icon Sets
- Histograms
- Moving Average
Predictive Analytics
- Correlation
- Regression - overview
- Regression - analysis
- Linear regression
- Multiple regression
Probability
- Probability I
- Probability II
- Binomial Probability
- Poisson Probability
Prescriptive Analytics I
- What If Analysis
- Data Table (3 variables)
- Scenario Manager
- Scenario Manager - Pivot
Data Visualization II
- Sparklines
- Color Scales
- Drawing Shapes
- Pivot Tables
- Pivot Charts
Prescriptive Analytics II
- Solver - overview
- Linear Programming
- The Solver model
- Non-Linear Programming
- Evolutionary Solver
Taught by
Garfield Stinvil, Colin Jaffe, and Brian McClain
