Day 27: Statistics for Business Applications

• Last Time: Testing the difference in two proportions (especially M&Ms!)

• Test Thursday: sections 12.1,2,4; 13.1,2,4

• Homework 13.6 due Thursday

• Return 13.4 homework:
  • 13.67
  • 13.70

• Today:
  • Review for the test:
    • From the objectives
    • Formulas
    • Why t-tests?
    • Reading t-tables
    • Proportions stick with z-tests.
    • Finding confidence intervals and testing hypotheses
    • Interpreting Minitab output
    • Don't forget about old stuff!

  • Introduction to linear regression: "...to predict the value of one variable on the basis of other variables."
    • Example: Heights of NKU students: males versus females.
      • To capture the "distance" (in minutes) for the one person who didn't give a time, I used linear regression on the data that four people provided.

    • Example: Predicting test scores based on homework (here's the data):
      • 6 homework averages and the test means
      • with the regression equation
      Of what value is homework? "Each point higher on homework (out of 100) means .3 points higher on the tests (out of 100)...."

    • Example: 18.8, p. 614

    • What's going on? How does linear regression work?
      • Do scatter plots indicate a linear relationship?
      • "Correlation" measures a linear relationship.
      • How do we find a "best-fit" line?
      • How good is that line?

• Next time: Test 3

Links:

• A nice on-line course about regression