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  • This tutorial includes using, finding, weighting, and solving problems with Moving Averages.
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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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  • This interactive tutorial on Exponential Smoothing helps learners understand the use of exponential smoothing, define exponential smoothing, cite the merits and demerits of exponential smoothing, and solve exercise problems using exponential smoothing.
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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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  • This interactive module helps students to understand the definition of and uses for clustering algorithms. Students will learn to categorize the types of clustering algorithms, to use the minimal spanning tree and the k-means clustering algorithm, and to solve exercise problems using clustering algorithms.
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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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  • The goal of this assignment is to obtain summary statistics for the variables in the data set, ncbirth1450.xls, which represents a random sample of 1450 births from the state of North Carolina.
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  • The assignment begins with creating a summary of and tables for the data, then walks the student through the steps of creating a hypothesis testing report. It uses the data set ncbirth200.xls, which is a random sample of 200 births from the data set ncbirth1450.xls.
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  • This introductory tutorial for SPSS 10.1 and 11.0 for Windows explains how to enter and summarize data and groups of data and to generate graphs.
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  • This activity guides students through the process of checking the validity of data, performing summary analysis, constructing box plots, and determining whether significant differences exist. The data comes from a study of mineral levels in older adults and is available in Minitab, Excel, SAS, and text formats.
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