Take an online tour through causal-comparative research designs, control procedures, and data analysis techniques. (
http://www.mnstate.edu/wasson/ed603/ed603lesson12.htm
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Helpful charts contrast causal-comparative, correlational, and experimental research. Visit the menu items at the left to view research examples and reflection questions. (
http://coe.sdsu.edu/ed690/mod/mod10/default.htm
)
Describes types of t-tests, determining statistical significance, and type I and type II errors. Links to an Excel spreadsheet that calculates t-values and other relevant information. (
http://www.statcan.ca/english/edu/power/ch9/scattergraphs/scatter.htm
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This applet lets you explore type I error and power of t tests (and two-group analysis of variance). Change the skew to investigate the effect of violating the normality assumption. Change the population standard deviations to investigate the effect of violating the assumption of homogeneity of variance. Press the "Begin" button to start the simulation. (
http://www.ruf.rice.edu/~lane/stat_sim/robustness/index.html
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The Center for Educational Technologies at Wheeling Jesuit University includes on their Web site a database of their educational research articles. Design, Development, and Implementation of an Inquiry-Based, Technology-Rich, Science Curriculum is one example of causal comparative research. (
http://www.cet.edu/research/papers/curriculum/main.html
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