Course Home Page
- Randall Pruim
office: North Hall 284
phone: (616) 526-7113 (but email is generally preferred)
- Time & Location
Monday, Tuesday, Thursday, Friday 9:00-9:50, in North Hall 259
- Office Hours
- I will maintain an email list of all students registered in this class
and will use it to distribute information and reminders of
various things pertaining to this course.
If you prefer to read your email from an account other than your Calvin
student account and do not have it set up to forward automatically,
send me email with the email address you prefer.
Please check your email daily.
You are responsible for any information communicated via email.
- Web Pages
In addition to this home page,
I will also maintain a list of web resources pertaining to this course.
You are responsible for any information appearing on the course
Items I have prepared and maintain online include
- a customizable calendar
of daily readings, lecture topics, exams, homework etc.
Monday, 03-Feb-2014 10:23:09 EST.)
- a list of homework assignments and due dates.
- information about tests and exams
(appearing shortly before each test date).
For quick access to these and other resources, see the navigation
bar at the top of this page.
If you are having difficulty with any portion of the course,
do not hesitate to see me.
Do this as soon as possible, certainly well in advance of any
deadlines (like tests) so that we can work to fix the problem.
The required text for this course is
Statistics: Unlocking the Power of Data
by Lock, Lock, Lock, Lock, and Lock
- Grading will be based on the
following approximate weighting:
Tests should be taken when they are scheduled.
I do not generally offer make-up, alternate or late tests.
Instead, if you miss one test (for any reason) or if your final exam
score is better than your worst test, then your final exam score will be
substituted for that test.
Modern statistics is done using modern technology. In this class we will
make use of three technologies
- R and RStudio will be our primary statistical tool.
R is a language and environment for statistical computing and graphics.
RStudio is an integrated development environment (IDE) for R that makes R
easier to use and provides a number of additional features, including
The use of R has become increasingly widespread in a wide range of disciplines,
including biology and public health. Among the high quality statistical packages,
it is the only one that is free and open source.
- the option of working "in the cloud" (think Facebook for statistics) or
on your local computer (free download and easy installation)
- support for reproducible research methods that allow the user to
create documents that contain R instructions, statistical analyses, plots,
and text all in one document that can easily be regenerated should the data
- nice interfaces for some common operations (e.g., loading data)
- Statkey applets will be used to illustrate
concepts, especially those related to resampling methods.
- Excel will be used primarily for data entry. Excel is
a very good tool for statistical analysis (it is missing many
things, actually gets some things wrong, and encourages bad habits of
mind), but it does provide an easy way to enter data and perform some very
basic data manipulations. One must be careful to use Excel well, and we'll
talk about good ways to use Excel to maintain data.
There are, by the way, a number of other statistics packages. But most of them
are expensive, so they aren't viable options for this course. The good news
is that once you use one statistics package, it is usually not too difficult
to migrate to another tool if you need or want to.
Occasionally there are special circumstances that require that the rules
and guidelines above be adjusted for a particular student.
In such cases, it is the responsibility of the student to inform me
of the situation as soon as possible, so that the appropriate
arrangements can be made. This includes, but is not limited to,
students with documented disabilities.
This page maintained by:
Friday, 27-Sep-2013 08:33:37 EDT
Department of Mathematics and Statistics