Limit Theorems

  • This applet was designed to illustrate the impact on simple linear regression output caused by adding a new data point. The applet simulates data and provides a graphical display of the data points and fitted regression line as well as the updated regression line after the addition of a data point.
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  • This FLASH based applet illustrates the sampling distribution of the mean. This applet allows the user to pick a population from over 2000 pre-defined populations. The user can then choose size of the random sample to select. The applet can produce random samples in one, 10, 100, or 1000 at a time. The resulting means are illustrated on a histogram. The histogram has an outline of the normal distribution and vertical lines at 1, 2, and 3 standard deviations. The applet can be viewed at the original site or downloaded to the instructors machine.
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  • Song incorporates various terms from areas such as experimental design, graphing, and hypothesis testing. May be sung to the tune of "Desperado" (The Eagles). Musical accompaniment realization are by Joshua Lintz and vocals are by Mariana Sandoval from University of Texas at El Paso.

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  • During this simulation activity, students generate sampling distributions of the sample mean for n = 5 and n = 50 with Fathom 2 and use these distributions to confirm the Central Limit Theorem. Students sample from a large population of randomly selected pennies. Given that the variable of interest is the age of the pennies, which has a geometric distribution, this is a particularly convincing demonstration of the Central Limit Theorem in action. This activity includes detailed instructions on how to use Fathom to generate sampling distributions. The author will provide the Fathom data file upon request.
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  • This activity uses a computer program to explore probability concepts such as sample space, independent events, law of large numbers, and reliability. An outline of the activity and the computer program are provided.
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  • This program allows the student to explore the nature of sampling distributions of sample means and sample proportions. The software provides separate windows for building population distributions, drawing and viewing random samples from the population, exploring the behavior of sampling distributions of sample means, and exploring the behavior of confidence intervals.
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  • This applet simulates randomly assigning newborn babies to families and measures the number of matches, or instances when a baby is assigned to its real family. The applet keeps track of each trial and records the information in a histogram. The idea is to teach theoretical values associated with random sampling. The relation website is a worksheet activity to accompany the applet.
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  • Using a parameter it's possible to represent a property of an entire population with a single number instead of millions of individual data points. There are a number of possible parameters to choose from such as the median, mode, or interquartile range. Each is calculated in a different manner and illuminates the data from a different point of view. The mean is one of the most useful and widely used and helps us understand populations. A population is simulated by generating 10,000 floating point random numbers between 0 and 10. Sample means are displayed in histograms and analyzed.
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  • This is a virtual applet, which models repeaded coin tossing by a random number generator. It allows you to change the number of tosses as well as runs and records your results.
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  • This general, introductory tutorial on mathematical modeling (in pdf format) is intended to provide an introduction to the correct analysis of data. It addresses, in an elementary way, those ideas that are important to the effort of distinguishing information from error. This distinction constitutes the central theme of the material described herein. Both deterministic modeling (univariate regression) as well as the (stochastic) modeling of random variables are considered, with emphasis on the latter. No attempt is made to cover every topic of relevance. Instead, attention is focussed on elucidating and illustrating core concepts as they apply to empirical data.
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