Lesson 1: Introduction to Advanced Statistics

Tue, Jan 17

Presentation:

• Attendance
• Intro to Advanced Statistics
  • Course Syllabus (PDF): S17-Syllabus-BUSAD360-AdvStats-Holman
  • Here’s the format my syllabus is supposed to be in: appendix-b-syllabus-template
  • Progression
    • By hand
    • Google Sheets
    • Google Sheets + XL Miner Add-On
    • Python (maybe)
• Resources
  • Textbook link to purchase on Amazon
  • Google Sheets
  • Follow me on Twitter and use #PuebloStats

• Linear Regression
  • Find a line of best fit for a set of points
  • Least Squares Regression Proof: MethodLeastSquares
  • Example: Beer Party
    • Use temperature to predict 12-packs consumed
    • Data from previous parties (Temp degrees F, 12-packs consumed)
      • Party 1: 60°, 10 12-packs
      • Party 2: 70°, 12 12-packs
      • Party 3: 80°, 20 12-packs
      • Party 4: 90°, 40 12-packs
    • Scatter Plot
    • Table setup
  • Sum of Squares calculations
    • SSxx = ∑x² – (∑x)²/n
    • SSyy = ∑y² – (∑y)²/n
    • SSxy = ∑xy – (∑x*∑y)/n
    • Demonstrate Calculations
      • Beer party data: {(60,10), (70,12), (80,20), (90,40)}
      • Another example: {(2,3), (4,6), (7,9), (11,12)}

Activity:

• Calculate Sum of Squares (SSxx, SSyy, SSxy)
  • Data set 1: {(3,5), (5,8), (8,11), (12,10)}
  • Data set 2: {(50,12), (60,15), (70,20), (80,30)}