In this course, we will use current events, guest lectures, and personal experiences, to examine fundamental statistical and probabilistic concepts as they appear in daily life. By the end of the course, you will be able to critically analyze the statistics you come across in your day-to-day life. Throughout the course, you will produce and analyze statistical information of your own. You will also evaluate other students' analyses.

We may view statistics as the organization and analysis of data. The following quantity would be an example of a statistic: the percentage of people in the US who own a pinball machine. There are several useful statistical ideas which we will explore in this course, including the average, the standard error, and the correlation coefficient. Sometimes a statistic is best understood with a picture as opposed to a number, and we will study such visual aids including: the histogram, the scatter plot, and the regression line.

Probability may be viewed as an attempt to understand randomness. For example, one might use probability to make sense of the following question: If you chose a person in the US at random, what is the chance that they own a pinball machine? We will explore several probabilistic concepts, including that of model, expected value, variance, confidence intervals, along with certain explicit models including the binomial model, normal distributions, and the models which arise in various gambling situations.

Many of the issues explored in Chance lie at the intersection of statistics and probability. For example, you might interview 1,000 US citizens and ask them "Do you own a pinball machine?" and then collect the following statistic: the percentage of these 1,000 people who own a pinball machine. Suppose 8% of those interviewed answered yes. With what right do you have to claim that 8% of the US population owns a pinball machine? To answer this, one has to understand how to give a statistic meaning with probability, which can be quite a tricky business. Information will be presented to you in this form throughout your life, and it is likely that you will make decisions based on such information. The primary goal of this course to help you better understand such information, allowing you to make more educated decisions in situations where statistics arise.

**Assignments and Grading:** Your grade for the course is based on
individual and group projects, a critique of other students' work,
class participation, and weekly quizzes.
60% of your grade
for the course will be based on three projects.
The two of these projects are
individual projects, the first worth 10% of
your grade and a final project worth 25% of your grade.
The there will also be
a group project, conducted by several students
working together, worth 25%
of your grade.
The remainder of your grade will be based on your critique of another
groups' presentations (15%), your participation in the course (10%),
and weekly quizzes (15%). All assignments due dates and
announcements will be posted in the
Class Log.

**Text:** __ A Self-teaching Guide, Statistics __, by Donald
J. Koosis,
available in the Dartmouth Bookstore.

**Computing:** We will be computing and organizing data with the
help of
the *Excel* and* Maple* programs, both of which are available
on Public.
Everyone should make sure that they have access to a computer running
both these
programs.

**Chance Web Site:** A lot of interesting information can be found
at the
the Chance web site, http://dartmouth.edu/~chance/.

**Honor Policy:** Collaboration is encouraged during all phases of
this
class, excluding the writing up of your individual projects and
critique. That
said, you **must** indicate all collaboration on an assignment when
it is
handed in, and give credit to the people involved.

**Students with Disabilities:** We encourage students with
disabilities,
including invisible disabilities, like chronic diseases and learning
disabilities,
to discuss with us any appropriate accommodations that might be helpful.
You
should do this by the end of the second week of the term, to ensure that
we
will have time to devise a workable solution. You should also contact
the Academic
Skills Center in 301Collis. All discussions will be confidential between
the
student and the two instructors, although we may need to consult the
Academic
Skills Center to verify registration for their services, and to discuss
appropriate
implementation. Please do not wait to come talk to us; we want to
provide an
optimal learning environment; to do this, we need information from you.