Reading Notes: Module 3 STAT 212
Sect. 3.3: The material in this section lays the foundation for the statistical analysis that will be
done throughout course, so it should be read carefully.
•The distinction between a parameter and a statistic is important. Really important. Be
sure that you understand it.
•The notion of a sampling distribution is also central, so read the definition and examples
closely.
•The graphic illustrating different degrees of bias and variability in Figure 3.11 is quite
informative.
Sect. 3.4: This section is not treated in lecture, so should be read thoroughly. (Even if you cannot
envision yourself ever behaving ethically.)
•The case studies presented in this section are particularly interesting.
•The terminology in this section shows up on homework and quiz questions.
Sect. 4.1: This is a short section that introduces the idea of probability.
•Randomness and independence are important concepts.
•If you have some spare time, you can replicate the coin tossing experiment described in
Example 4.1.
Sect. 4.2: This section is treated fairly thoroughly in lecture, but you should still read over it.
•Be sure that you know and understand the Probability Rules — they will show up in
numerous homework and quiz questions.
•There is a videoclip on the Module Resources page demonstrating how to compute
probabilities from density curves.
•The last subsection on Normal probability models should look familiar. This is the
Normal distribution that we encountered in Section 1.3.
Sect. 4.3: We only cover part of this section in this module. We stop just before “The mean of a
random variable” on page 271.
•The definition of random variable (and the distinction between discrete and continuous
random variables) is central.
•Be sure that you understand the definition of probability distribution as it relates to
random variables.
•Example 4.12 gives a nice intuitive explanation for why continuous probability distribu-
tions assign probability 0 to every individual outcome.