Course description
STAT 101-3 Introduction to Statistics.
An introductory course in research methodology and associated
statistical analysis techniques. (3-1-0)
Prerequisite:
Prerequisite:
BC Math 11 (or equivalent) or Basic Algebra. Students with credit for
ARCH 376, BUEC 232 (formerly 332)
or STAT 270 (formerly MATH 272 and
371) may not subsequently receive credit for STAT 101-3. Students with
credit for STAT 102, 303 (formerly STAT 103), 301, MATH 101 or 102 may
not take STAT 101 for further credit.
Textbook:
The Basic Practice of Statistics, 2nd Ed.
by David S. Moore, publisher: WH Freeman & Co.
Optional: JMP IN software package.
Outline:
Aimed at a non-mathematical audience, this course discusses
procedures that are most commonly used in the summary of
statistical surveys and in the interpretation of experimental data.
The rationale for these procedures is explained in detail, but the
use of mathematical formulas is kept to a minimum.
Either STAT 101 or STAT 201 is a satisfactory prerequisite for STAT 302.
The course will include an introduction to JMP IN, a computer package
for statistics. You will need access to a computer and to JMP IN
to complete the course.
- Data summaries and displays: Graphical displays, measures
of
central tendency, measures of dispersion, percentiles, the normal curve,
computer-generated graphs and data summaries.
- Summarizing the relationship between variables: Scatterplots,
the regression line, correlation, and causation.
- The research process: Assembling background
information,
formulating hypotheses, generating informative data with
controlled
experiments and randomized surveys, and using the data to reassess
hypotheses.
- Case studies involving happenstance data, randomized
surveys,
and controlled, randomized experiments.
- Basic probability calculations: The addition and
multiplication rules, and independence.
- Distributions for count data: The binomial and Poisson
distributions; where they arise, and their basic properties.
- Hypothesis tests and confidence intervals: p-values,
confidence levels, and their interpretation; inferences on a
proportion and a mean based on the standard normal and
t-distributions,
underlying assumptions, and a mention of alternatives.
- Comparing two treatments: Completely randomized and
paired
designs; associated standard normal and t-tests.
- Inference on the relationship between two variables:
Simple linear regression and correlation analysis, plus, if
time permits, comparing two lines and basic analysis of
covariance.
- Comparing several treatments: Completely randomized
and randomized block designs; one- and two-way analyses of
variance.
- Analyzing Frequency Counts: tests for homogeneity
and
independence.
Grading policy:
| Homeworks: |
20% -- 5 assignments, best 4 of 5 weighted equally |
| Midterm: |
30%
|
| Final: |
50% -- or 80% if you do better on the final than on the midterm |
Students should be aware that they have certain rights to
confidentiality
concerning the return of course papers and the posting of marks. Please
pay careful attention to the options discussed in class at the beginning
of the semester and be sure to fill out the information
in the Class Database
form before the first homework is due.