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View Resource Against All Odds: 26. Small Sample Inference for One Mean

In this free online video, students discover an improved technique for statistical problems that involves a population mean: the t statistic for use when sigma is not known. Emphasis is on paired samples and the t confidence test and interval. The program covers the precautions associated with these robust t procedures, along with their distribution characteristics and broad applications."
View Resource Against All Odds: 25. Tests of Significance

This free online video program "explains the basic reasoning behind tests of significance and the concept of null hypothesis. The program shows how a z-test is carried out when the hypothesis concerns the mean of a normal population with known standard deviation. These ideas are explored by determining whether a poem "fits Shakespeare as well as Shakespeare fits Shakespeare." Court battles over...
View Resource Against All Odds: 15. Designing Experiments

In this free online video program, students will learn that "statistics can be used to evaluate anecdotal evidence. This program distinguishes between observational studies and experiments and reviews basic principles of design including comparison, randomization, and replication. Case material from the Physician's Health Study on heart disease demonstrates the advantages of a double-blind...
View Resource Against All Odds: 21. Binomial Distributions

This free online video program "discusses binomial distribution and the criteria for it, and describes a simple way to calculate its mean and standard deviation. An additional feature describes the quincunx, a randomizing device at the Boston Museum of Science, and explains how it represents the binomial distribution."
View Resource Against All Odds: 24. Confidence Intervals

This free online video program "lays out the parts of the confidence interval and gives an example of how it is used to measure the accuracy of long-term mean blood pressure. An example from politics and population surveys shows how margin of error and confidence levels are interpreted. The program also explains the use of a formula to convert the z* values into values on the sampling...