|
|
|
|
Course
|
Introduction to probability and the
concepts of estimation and hypothesis testing for use in
experimental, social, and professional sciences. One and two-sample
analyses, nonparametric tests, contingency tables,
sample surveys, simple linear regression, various statistical packages
including SAS, SPSS, Minitab, and R. |
| Purpose |
To provide future scientists in these
fields with a base on which to
build a continually expanding array of methods for experimental design
and data analysis. Students will ideally come away with:
(1) an
understanding of basic probability and the manner in which all formal
statistical inference depends on it;
(2) the ability to carry out the
basic analyses listed in the description using widely available
software;
(3) a knowledge of the universal principles underlying all
hypothesis testing and interval estimation, thereby
facilitating
interactions with professional statisticians. |
| Textbook |
Introduction to the Practice of Statistics (5th edition),
by D.S. Moore and G.P. McCabe, W.H. Freeman and Co., 2006. |
| Grading |
Grading (%): A 90; B+ 87; B
80; C+ 77; C 70; D+ 67;
D 60; F
<60;
|
| Software |
One statistical package of your choice:
SAS, SPSS, Minitab, R, or other package
|
| Topics |
Data description and
graphical representation
|
| Probability,
discrete random variables, binomial distribution |
| Continuous random
variables, the normal distribution |
| Sampling |
| Sampling distributions, the
central limit theorem |
| Estimation,
confidence intervals |
| Hypothesis
testing |
| Comparing two treatments or
populations |
Categorical data analysis
|
| Correlation and simple
linear regression |
Two-way tables analysis
|
|
|
|