(*Note: Though this class is primarily focused on learning and manipulating data using the SAS or JMP statistical packages, I will be programing and posting solutions in R. I may try to post equivallen solutions in SAS simultaneously for those that are interested in learning both. R is free and does not require 22 Gazigabytes. )
T-Test:
History for the nerds-
http://en.wikipedia.org/wiki/William_Sealy_Gosset
Basic t-test with calculator-
http://www.stattools.net/tTest_Exp.php
More detailed explanation-
http://simon.cs.vt.edu/SoSci/converted/T-Dist/activity.html
Regression + ANOVA = ANCOVA
Regression:
covariance = 
regression coefficient = 
(*Note: The n or n-1 will cancel when the cov is divided by the var, thus whether the correction is applied or not is irrelevant)
Regression explained:
http://www.law.uchicago.edu/files/files/20.Sykes_.Regression.pdf
more simply:
http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm
http://easycalculation.com/statistics/learn-regression.php
And explained well:
http://www.sjsu.edu/faculty/gerstman/StatPrimer/regression.pdf
Goodness of fit explained:
http://www.mathworks.com/help/curvefit/evaluating-goodness-of-fit.html
Regression in SAS:
http://www.ats.ucla.edu/stat/sas/webbooks/reg/chapter1/sasreg1.htm
http://www.youtube.com/watch?v=Bzm8TJYFZcs
Regression in R
http://msenux.redwoods.edu/math/R/regression.php
Model I and II regressions:
http://www.mbari.org/staff/etp3/regress/about.htm
WOOOOO!
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