Day 13: Statistics for Business Applications

Tuesday, 3/23,
to
Thursday 3/25?

I'm going to be out of town on Thursday, and the easy thing would be for me to get a proctor, rather than someone to teach the class.

• Point estimators versus interval estimators
• Unbiasedness and consistency
• Relatively efficient estimator
• Basic idea of confidence interval estimator of mu (p. 302)
  • We're going to build a cage around a point estimator, that we hope captures the parameter.
  • Using a wider cage means you're more likely to catch it, but by using a larger cage you're not so sure exactly where it is!
  • You want to be right a goodly amount of the time (e.g. 90%, 95%).
• We worked example 10.54

• Return homework 9.1-9.2

• Collect homework 9.3

• Applet #15

• sections 10.1-10.3 - Confidence Intervals
  • Example: 10.53, p. 313

• section 10.4 - Computing sample size from a desired interval
  • Example: 10.81
  • Example: 10.66