Statistics 50 Course Outline
This course roughly divides into four segments. We will cover approximately
one chapter each lecture (that's 3 chapters per week.) Below is a rough
outline. Changes may be made during the quarter.
- Collecting and Describing Data
``Garbage in, garbage out;SPMquot; applies to more than software; it's also true
of science that if the data are poor, the conclusions will also be
suspect. What, then, constitutes good data? And how do you summarize
this data once you've collected it?
- Chapter 1, Controlled Experiments
- Chapter 2, Observational Studies
- Chapter 3, The Histogram
- Chapter 4, The Average and the Standard Deviation
- Chapter 5, The Normal Approximation for Data
- Probability
Probability is the foundation of Statistics. We'll talk about how
chance interferes with our observations, and explore some properties
of the laws of chance.
- Chapter 6, Measurement Error
- Chapter 13, What are the Chances?
- Chapter 14, More about Chance
- Chapter 16, The Law of Averages
- Chapter 17, The Expected Value and Standard Error
- REVIEW
- MIDTERM I
- Chapter 18, The Normal Approximation for Probabability Histograms
- Inference
Does smoking cause lung cancer? Is the ``protease cocktail" an effective
treatment for AIDS? Is the mean global temperature rising? These are
all examples of inference based on data, and we'll cover some basic
inference techniques.
- Chapter 19, Sample Surveys
- Chapter 20, Chance Errors in Sampling
- Chapter 21, The Accuracy of Percentages
- Chapter 23, The Accuracy of Averages
- chapter 26, Tests of Significance
- Chapter 27, More Tests for Averages
- Chapter 28, The chi-squared-Test
- Chapter 29, A Closer Look at Tests of Significance
- Chapter 8, Correlation
- REVIEW
- MIDTERM II
- Chapter 9, More about Correlation
- Chapter 10, Regression
- Chapter 11, The RMS Error for Regression
- Chapter 12, The Regression Line
- REVIEW for final
- FINAL, June 9, 11:30 am.