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Statistical Topic

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  • 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 discrimination in hiring provide additional illustration.
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  • This is a free online video program. "How to recognize a two-sample problem and how to distinguish such problems from one- and paired-sample situations are the subject of this program. A confidence interval is given for the difference between two means, using the two-sample t statistic with conservative degrees of freedom."
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  • 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."
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  • In this free online video program, "a two-way table of counts displays the relationship between two ways of classifying people or things. This program concerns inference about two-way tables, covering use of the chi-square test and null hypothesis in determining the relationship between two ways of classifying a case. The methods are used to investigate a possible relationship between a worker's gender and the type of job he or she holds."
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  • This demonstration allows you to view the binomial distribution and the normal approximation to it as a function of the probability of a success on a given trial and the number of trials. It can be used to compute binomial probabilities and normal approximations of those probabilities.
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  • As described on the page itself: "The simulation shows a scatterplot of data from a bivariate distribution in which the relationship between the two variables is linear. You can change the "input" values of slope, standard error of the estimate, or standard deviation of X for this data sample, and see the effects of your change. "
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  • In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.
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  • This applet shows how the correlation between two variables is affected by the range of the variable plotted on the X-axis.
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  • This applet demonstrates that even a "small" effect can be important under some circumstances. Applicants from two groups apply for a job. The user manipulates the mean and the cut-off score in order to see the effects the small changes has on the number of people hired in each group. The effects on the proportion of hired applicants from each group are displayed.(Requires a browser that supports Java).
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  • The applet allows users to sample from a normal distribution or from a uniform distribution. It shows the expected values and the observed values and computes the deviation. Then, a chi-square test shows if the deviations are significant for both the normal and uniform distributions.
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