Holcombe:Statistics

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 Revision as of 15:35, 23 March 2010 (view source)← Previous diff Revision as of 18:29, 9 June 2010 (view source) (→Bootstrapping)Next diff → Line 21: Line 21: *Using MacCurveFit for OS9; rarely used *Using MacCurveFit for OS9; rarely used ==Bootstrapping== ==Bootstrapping== + how I [[Holcombe:fit psychometric functions]] and bootstrap + [http://www.uvm.edu/~dhowell/StatPages/Resampling/BootstMeans/bootstrapping_means.html Howell's] pages [http://www.uvm.edu/~dhowell/StatPages/Resampling/BootstMeans/bootstrapping_means.html Howell's] pages == == == == [[Holcombe:CircularStatistics|Circular Statistics]] [[Holcombe:CircularStatistics|Circular Statistics]]

Revision as of 18:29, 9 June 2010

Members

Alex Holcombe
Sarah McIntyre
Fahed Jbarah
• Shih-Yu Lo
• Patrick Goodbourn
Lizzy Nguyen
Alumni

Other

The picturing of data allows us to be sensitive not only to the multiple hypotheses that we hold, but to the many more we have not yet thought of, regard as unlikely, or think impossible -- Tukey, 1974

The great fun of information visualization is that it gives you answers to questions you didn’t know you had -- Ben Shneiderman

Jody Culham error bars lecture "Rule of thumb for 95% CIs: If the overlap is about half of one one-sided error bar, the difference is significant at ~ p < .05 If the error bars just abut, the difference is significant at ~ p< .01 works if n >= 10 and error bars don’t differ by more than a factor of 2 "

"If events are dependent (whether causal or not), the aggregate is not going to be Gaussian. "- why?

the sum of two independent random variables is distributed according to the convolution of their individual distributions

Fitting curves to data

• R is often used in the lab
• Python alone and with SciPy can be used easily, example here
• MATLAB is sometimes used
• Using MacCurveFit for OS9; rarely used

Bootstrapping

how I Holcombe:fit psychometric functions and bootstrap

Howell's pages

Circular Statistics