

Connections
• Probability
 This unit centers around probability and, like the previous
unit, it stresses the importance of how the probabilities associated
with values in a random experiment (which we model using pdfs in this
unit) differ from the relative frequencies of values found within
populations (which we’ve modeled using mathematical functions in
previous units).
 Simulating probabilities is also a very powerful tool and
is referenced briefly in this unit. The following unit will expand more
on this topic.
• Models
 Many probability models are referenced in this unit, but a
lot of the examples you might use will refer back to the normal model
in particular. This model will continuously be referenced in future
units.
 As discussed in earlier units, one can identify what
distribution is appropriate to model a situation by describing
distributional characteristics such as the shape, center and spread.
• Inference
 As referenced in the previous unit, modeling probabilities
is a key piece to statistical inference to determine whether a sample
statistic is typical or unusual under the assumption of a particular
model. This unit attempts to make this connection more clear and in
future units, this point will be even more explicit.
