|
Math 121 Elementary Statistics Fall 2000
| Instructor: |
Allan Rossman |
| Office: |
New Science Building 235 (x-1668) |
| Office hrs: |
M 1:00-3:00, W 2:00-4:00 (and by appointment and by chance) |
| E-mail: |
rossman@dickinson.edu |
| Meetings: |
TuTh 9:30-10:45, New Science Building 121 |
| Text: |
Workshop Statistics: Discovery with Data (2nd edition) |
Click here to see the listing of regular
assignments and here to see instructions
for the special assignments.
Overview:
Statistics might be defined as the science of numerical reasoning from
data. Its purpose is to aid people in making decisions based on the analysis
of numerical information. Data and numerical arguments abound not only
in science and social science disciplines but in almost every field of
academic inquiry. Moreover, most people encounter statistical reasoning
in everyday life. It is therefore exceedingly appropriate and important
for all liberally educated citizens to undertake study of fundamental principles
and methods of statistics.
Course Principles:
The following principles guide my teaching of this course and may help
you to understand what I think the course is about:
-
Statistics is not number-crunching. Contrary to its popular perception
as a black box collection of arcane magic tricks, statistics involves much
more than numerical computations. The emphasis of the course will be on
understanding statistical concepts and on interpreting and communicating
the results of statistical analyses. In other words, you will be expected
to learn to construct and analyze numerical arguments. In contrast to most
mathematics courses, we will be using phrases such as "there is strong
evidence that ..." and "the data suggest that ..." rather than "the exact
answer is ..." and "it is therefore proven that ...". To alleviate the
computational burden, we will often use the computer program Minitab to
perform calculations and produce visual displays.
- Statistics involves the analysis of genuine data. Supporting my
contention that statistics is applicable in everyday life and in most fields
of academic endeavor, you will analyze genuine data from a wide variety
of applications throughout the course. Many of these data sets involve
information that you will collect about yourselves and your peers; others
will come from sources such as almanacs, journals, magazines, newspapers,
and books. The contexts for these data will span a wide variety of subject
matter; most should be of interest to a general audience.
-
Understanding results from investigation and discovery. As opposed
to passively taking notes while I lecture, you will spend the vast majority
of class time actively engaged with the material. You will work through
activities carefully designed to lead you to discover fundamental statistical
ideas for yourself. You will be encouraged to work collaboratively with
a partner on most of these activities, and some will require the use of
the computer. My role during class time will be to mill about the classroom,
answering your questions and prodding you toward a better understanding
of the material. I will also lead class discussions and present explanations
where appropriate.
Course Goals:
My primary goals for this course are to help you to develop:
-
the ability to apply and interpret the results of a variety of statistical
techniques, including both exploratory and inferential methods;
- an understanding of many of the fundamental ideas of statistics,
such as variability, distribution, association, causation, sampling, experimentation,
confidence, and significance;
-
a critical perspective with which to analyze and assess statistical
arguments such as one encounters in the popular press as well as in
scholarly publications.
Prerequisites:
There are no formal prerequisites for this course. Certainly, no prior
knowledge of statistics is expected. The mathematical level of the course
is that of high school algebra. Although we will use computers extensively,
you need not have prior familiarity with them. I will provide you with
instructions concerning the use of the computer and the statistical analysis
package Minitab. What you do need to bring to the course are an
open mind for tackling quantitative questions in a conceptual manner and
a willingness to participate actively in class.
Grading:
Your course grade will be determined by your work on:
-
regular homework assignments (10%)
-
two special assignments (5% each)
-
two midterm exams (25% each)
-
a final exam (30%)
You are encouraged to work together on the assignments, but your answers
must
be written up individually in your own words. Some assignments require
the use of the computer, so this classroom is available for you from 7-11pm
Sunday-Thursday and some other times as well. The assignments will be collected
for grading periodically, and no late assignments will be accepted without
a written medical excuse. Your lowest two scores on the assignments will
be dropped from the calculation of your score. A listing of assignments
and due dates will be available here.
Two special assignments will be given. These will involve more extensive
and independent work than regular assignments. They will ask you
to analyze data that you find or collect yourself and will also require
a thorough write-up. No late special assignments will be accepted without
a written medical excuse, and no scores on the special assignments will
be dropped from the calculation of your score. A listing of assignments
and due dates will be available
here.
Dates for the exams will be announced in class at least one week in
advance. You may use your textbook for the exams; you should also bring
a hand calculator. Make-up exams will be given only with a written medical
excuse.
The final exam will concentrate on most recent material but will
also have a cumulative component. You should also be aware that most of
the course is cumulative in the sense that material presented later in
the course builds on earlier material.
Class attendance is strongly encouraged. Due to the interactive
nature of the classroom environment, most students find that attending
class regularly is essential to learning the material. Naturally, you are
responsible for material covered and announcements made during classes
that you miss.
Content:
We will cover all (or almost all) of the topics in the text, which are
arranged into six units:
| Unit I |
Exploring Data: Distributions |
| Unit II |
Exploring Data: Comparisons and Relationships |
| Unit III |
Collecting Data |
| Unit IV |
Randomness in Data |
| Unit V |
Inferences from Data: Principles |
| Unit VI |
Inferences from Data: Comparisons and Relationships |
Suggestions:
With apologies to David Letterman, I offer you the following "Top Ten"
suggestions as you approach this course:
| 10. Come to class. |
9. Ask questions. |
8. Use office hours. |
| 7. Don't get behind. |
6. Don't get overconfident. |
5. Work together. |
| 4. Read carefully. |
3. Write well. |
2. Have fun! |
| 1. Think!! |
A common theme emerges from this list: You are responsible for your
own learning. As your instructor, I view my role as providing you with
contexts and opportunities which facilitate the learning process. Please
call on me to help you with this learning in whatever ways I can.
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