STAT WEBLINKS
| These links were originally compiled and described by RBT and Karima Zedan. In the current version this page includes links and descriptions relevant to both UNDERgraduate statistics topics as well as GRADuate statistics topics in simple and multiple regression and related topics. |
| NOTE TO UNDERGRADUATES: Since this set of weblinks has been designed to serve BOTH graduate and undergraduate statistics courses, I have put a large U after a link that I think is particularly helpful for UNDERgraduates |
SITE: http://www.psychstat.smsu.edu/introbook/normal.htm U
or [EVEN BETTER]: http://www.psychstat.smsu.edu/pdf/pdfj.htm
PURPOSE: You can convert z scores to areas under the normal curve, or find the area under the normal curve corresponding to two different z scores. The SECOND url also does confidence intervals and other VERY, VERY cool stuff, AND shows you what is happening GRAPHICALLY. For the second site: MU = mean; SIGMA = standard deviation. To check out a z score distribution set MU=0 SIGMA=1 and enter your Z score.
If you are having trouble figuring out areas under the curve, this should prove helpful.
SITE: http://www.psychstat.smsu.edu/introbook/sbk00.htm U
PURPOSE: David Stockburger's award-winning, on-line introductory statistics textbook. Highly recommended for background reading
KEYWORDS:
Variables,
Normal Distribution, p-value, distribution tables, t-test
NOTE TO UNDERGRADUATES: This is an EXTREMELY HELPFUL, all purpose site, with lots of examples and definitions and such. After you enter the textbook (see below), take a look at the following links on the right hand side of the page - THESE ARE VERY USEFUL:
elementary concepts
basic statistics
statistical glossary
distribution tables
MULTIPLE REGRESSION
Click on the topic LINEAR REGRESSION from the textbook menu
1. Click on the first term under the table of contents on the right side of the screen
2.
Click on the underlined topic of interest from this page.
3.
Helpful subtopics with detailed answers to introductory questions
include:
1.
What are variables?
2.
Dependent vs. Independent Variables
3.
Measurement scales
4.
What is statistical significance (p-value)?
5.
Why the normal distribution is important?
1. Click on the second term under the table of contents on the right side of the screen.
2.
Click on the first and third bulleted headings, Descriptive
Statistics and t-test for independent samples for information
pertaining to these relevant topics.
1.
Scroll down the table of contents headings until Statistical
Glossary appears (sixth from the last selection) and click on it for a thorough
alphabetical listing of statistical terms.
1. Click on this topic from the table of contents for illustrations of various tables (third from the last selection).
2. The Z Table, t table and Chi-Square table may be of interest
SITE: http://trochim.human.cornell.edu/kb/contents.htm U
KEYWORDS:
Sampling,
Normal Distribution, t-test, Reliability, Validity, Survey, Scaling, Design, SIMPLE REGRESSION
NOTE TO UNDERGRADUATES: This is a very good site on the topic of SAMPLING THEORY.
All of the material is helpful here but for the purposes of this class, most relevant is the chapter GENERAL LINEAR MODEL under the section INFERENTIAL STATISTICS. This is a good explanation of the simple regression model in a graphical format.
Other, more basic stuff that may prove helpful:
From
the fourth heading, Sampling, all of the subtopics may be useful to you:
external validity, sampling terminology, statistical terms in sampling,
probability sampling and nonprobability sampling.
The
fifth heading, Measurement, provides the following useful subtopics:
construct validity, reliability, survey research, scaling and qualitative
measures.
The
sixth heading, Design, offers good explanations for the following:
internal validity and introduction to design.
The
seventh heading, Analysis, provides information regarding: descriptive
statistics (mean, standard deviation, correlation etc.) and inferential
statistics (t-test).
SITE: http://davidmlane.com/hyperstat/index.html U
OVERVIEW: This is the hyperstat program home page. They have an online tutorial.
UNDERGRADUATE. There is good material here, and good links to other sites. the textbook itself (see the chapters listed on the left) is a genuine ON LINE text, with some nifty demos.When you click on a chapter on the left, the chapter table of contents comes up. Some of them have demos. The demos may or may not work depending on whether you have java applets installed.
The middle column refers you to other web pages on the same set of topics.
The site does NOT appear to be searchable by key word.
GRADUATE
KEYWORDS: multiple regression
This page also links you to some other text sources as follows below. If some of the pages come up asking for a password, just click cancel, and the pages may still come up.
Text
Inferences
for regression
by H. J. Newton, J. H. Carroll, N. Wang, and D. Whiting
Multiple regression
by StatSoft
Regression by
G. David Garson.
Linear
regression, multiple
regression
by Sunkara, V. Patil, R. Bellary, G. Quisumbing, H. Le, and Z. Zhou
The general linear
model, Regression
toward the mean by William Trochim
Correlation
coefficient
by Will Hopkins of the University of Otago
SITE: http://www.dartmouth.edu/~chance/ U
The Chance project - some real world applications relevant to undergrad quantitative literacy course. Some interesting audio files as well, and some interesting data. For example, are NBA shooters gonna make the next free throw if they feel "hot?"
SITE: http://www.anu.edu.au/nceph/surfstat/surfstat-home/surfstat.html U
VERY COOL applets. Go to "hotlist for java applets"
KEYWORDS: mean vs. median; probability distribution
SITE: http://www.tufts.edu/%7Egdallal/LHSP.HTM U
"The Little Handbook of Statistical Practice"
Chapters in statistics by a biomed researcher. Some good chapters. Those on
"The basics" and "significance testing" are especially good.
SITE: http://www.exeter.ac.uk/~SEGLea/multvar2/multreg1.html
KEYWORDS: Multiple regression
OVERVIEW: Dr. Steven Lea, Department of Psychology, University of Exeter (England): Introduction to multiple regression course
SITE: http://www.exeter.ac.uk/~SEGLea/multvar2/multreg2.html
KEYWORDS: Multiple regression; dummy variables
OVERVIEW: More advanced issues in multiple regression from Dr. Lea.
SITE: http://www.windsor.igs.net/~nhodgins/multiple_regression_research_analysis.html
OVERVIEW: Some simple points about multiple regression.
SITE: http://m1.aol.com/imsap/MMR.html
KEYWORDS: interaction terms
OVERVIEW: Some comments on entering interaction terms, with some graphic backup, from Scott Petersen, someone with an MA in I-O psychology
SITE: http://m1.aol.com/imsap/homogeneity.html
KEYWORDS: assumptions, homogeneity of variance
OVERVIEW: Talks about homogeneity of variance assumption, also from Scott Petersen