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 Sampling SIM: Sampling Distributions Created by authors Beth Chance, Bob delMas and Joan Garfield, this webpage provides instructions for teaching sampling distributions using Sampling SIM software. It includes information regarding prerequisite knowledge, common misconceptions, and objectives, as well as links to an activity and a pre/post-test. This is a fairly comprehensive overview of the tools need for sampling distributions.... http://www.tc.umn.edu/~delma001/stat_tools/tools_samp_dist.h...
 Sampling SIM: P-values and Standard Distributions Created by authors Beth Chance, Bob delMas, and Joan Garfield, this webpage provides instructions for teaching p-values and standard distributions using Sampling SIM software. It includes information regarding prerequisite knowledge, common misconceptions, and objectives, as well as links to an activity and a pre/post-test. This resource provides a great assessment of skills gained by students... http://www.tc.umn.edu/~delma001/stat_tools/tools_p_value.htm
 Sampling SIM: Confidence Intervals Created by authors Beth Chance, Bob delmas and Joan Garfield, this web page provides instructions for teaching confidence intervals using Sampling SIM software. It includes information regarding prerequisite knowledge, common misconceptions, and objectives, as well as links to an activity and a pre/post-test. This resource will provide a nice assessment of the skills obtained during this lesson. http://www.tc.umn.edu/~delma001/stat_tools/tools_conf_intv.h...
 Tools for Teaching and Assessing Statistical Inference: Sampling SIM This website helps students learn concepts underlying statistical inference, through the simulation software, sampling SIM. This software lets students explore sampling distributions by building population distributions, taking random samples, and exploring the behavior of sampling distributions and confidence intervals. The site includes instructional modules and assessment instruments. http://www.tc.umn.edu/~delma001/stat_tools/
 Histogram Sorting Using Cooperative Learning This activity has two major goals: (1) to give students experience with a variety of histograms of data, and (2) to help them better recognize different shapes and characteristics. Too often students only see one or two perfect examples (e.g., normal, right skewed) and have a difficult time describing and classifying histograms of real data. This activity also helps students determine which... http://serc.carleton.edu/sp/cause/gallerywalk/examples/14043...
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