Spring 2018 – Advanced Statistics
BUSAD 360 Advanced Statistics Course page
- Lesson 25: Model Testing
- Lesson 24: Term Project Data Wrangling
- Lesson 23: The Home Stretch
- Term Project
- Exam 2 Redo Results
- Lesson 22: Bootstrap confidence intervals for linear regression
- Lesson 21: Bootstrap Confidence Intervals
- Lesson 20: Statistical Thinking in Python (Part 2)
- Lesson 19: Comparing Distributions with Seaborn
- Lesson 18: Quantitative Exploratory Data Analysis
- Lesson 17: Graphical Exploratory Data Analysis (Note: meet in HSB 120)
- Exam 2 Results
- Lesson 16: Review for Exam 2
- Lesson 15: Python Loops for Monte Carlo Simulation
- Lesson 14: Python Importing CSV files with Pandas
- Lesson 13: Python Data Graphics with Matplotlib
- Lesson 12: Using Python to Calculate Regression Estimates
- Lesson 11: Python Basics, Lists, Functions and Packages
- Lesson 10: Intro to Python for Data Science
- Lesson 9: Multiple Regression Variable Selection Procedures
- Lesson 8: Measuring Forecast Error
- Exam 1 Results
- Lesson 7: Review for Exam 1
- Lesson 6: Applied Regression Analysis (2 of 2)
- Lesson 5: Applied Regression Analysis (1 of 2)
- Lesson 4: Intro to Multiple Regression
- Lesson 3: Simple Linear Regression
- Lesson 2: Scatterplots and Correlation
- Lesson 1: Syllabus, Sheets and Trendlines
