Before we even start these chapters, understand that this course really has three different components: descriptive statistics, probability, and inferential statistics. See the overview page for more detail.

Chapter 1

1. Section 1.1
   • Population
   • Sample
     • Simple random sample (detailed discussion)
     • Sample of convenience (detailed discussion)
     • Stratified sample (detailed discussion)
     • Cluster sample (detailed discussion)
     • Systematic sample (detailed discussion)
     • Voluntary Response sample (detailed discussion)
   • a population parameter
   • a sample statistic (see the discussion page)
2. Section 1.2
   • data set Palay: Sets and Lists 4:47
   • Qualitative data
     • Nominal data
     • Ordinal data
   • Quantitative data
     • Discrete data
     • Continuous data
     Interval measures (not in text also see special palay pages)
   • Ratio measures (not in text)
   • new page on this material, taken from the R version of the course: data
3. Section 1.3
   • Experimental units (subjects)
   • Outcome (or response)
   • Treatments
   • Randomized Experiments (experimentor in charge)
   • Observational studies (experimenter merely observes)
   • Double-blind studies (Pygmalian effect)
   • Randomized Block experiment (see additional note on heart attacks)
   • Confounding
   • Types of Observational Studies
     • cohort studies
       • prospective cohort -- now and forward
       • cross-sectional cohort -- now
       • retrospective cohort -- from back then until now
     • Case-control studies
4. Section 1.4
   • Mathematical definition of "bias"
   • Sources of bias
     • voluntary response
     • self-interest
     • social acceptability
     • Leading question
     • non-response
     • sampling
5. Additional Material
   • Differences in TI calculators (see TI Versions)
   • Generating Random Values (see Random Numbers on the TI Calculators)