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14440CAUSEweb.orgen-useditor@causeweb.orgwebmaster@causeweb.orgMon, 1 Sep 2014 12:00:00 -0400Tue, 20 May 2014 12:00:00 -0400http://www.rssboard.org/rss-2-0-1Video: 500 Trials
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=2374A video to teach about the central limit theorem and various issues in one-sample hypothesis testing. The lyrics and video were created by Scott Crawford from the University of Wyoming. The music is from the 1988 song "I'm Gonna Be (500 miles)" by the Scottish band The Proclaimers. The video took second place in the video category of the 2013 CAUSE A-Mu-sing competition. Free for non-profit use in classroom and course website applications.Mon, 24 Jun 2013 02:12:08 -0400IDEAL Modules
http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1304
http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1304The modules in this collection discuss numerous statistical topics with examples and Java applets. Topics covered: Variable Types; Calculations; Histograms; Moments; Quantiles; Probability Definitions, Laws, and Simulations; Binomial, Poisson, and Normal Distributions, Normal Approximation to the Binomial, Central Limit Theorem, Confidence Intervals, Hypothesis Testing, Control Charts, Contingency Tables, Correlation, and Regression.Sun, 24 Feb 2013 10:07:30 -0500Sampling Distributions of the Sample Mean: A Fathom Project
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1798During 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.Sat, 30 Jan 2010 08:16:42 -0500Poem: The Normal Law
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1824"The Normal Law" is a poem whose words form the shape of the normal density. It was written by Australian-American chemist and statistician William John ("Jack") Youden (1900 - 1971). The poem was published in The American Statistician page 11 in v. 4 number 2 (1950).Fri, 12 Sep 2008 12:08:44 -0400Sampling distribution of the mean
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1793This 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.Sat, 26 Jan 2008 05:00:45 -0500*Using an Applet to Demonstrate a Sampling Distribution
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1761This in-class demonstration combines real world data collection with the use of the applet to enhance the understanding of sampling distribution. Students will work in groups to determine the average date of their 30 coins. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. The idea here is that students will remember what they physically did to create the histogram and, therefore, have a better understanding of sampling distributions.Sun, 25 Nov 2007 07:21:22 -0500General Central Limit Theorem (CLT) Activity
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1699This activity represents a very general demonstration of the effects of the Central Limit Theorem (CLT). The activity is based on the SOCR Sampling Distribution CLT Experiment. This experiment builds upon a RVLS CLT applet (http://www.ruf.rice.edu/~lane/stat_sim/sampling_dist/) by extending the applet functionality and providing the capability of sampling from any SOCR Distribution.Goals of this activity: provide intuitive notion of sampling from any process with a well-defined distribution; motivate and facilitate learning of the central limit theorem; empirically validate that sample-averages of random observations (most processes) follow approximately normal distribution; empirically demonstrate that the sample-average is special and other sample statistics (e.g., median, variance, range, etc.) generally do not have distributions that are normal; illustrate that the expectation of the sample-average equals the population mean (and the sample-average is typically a good measure of centrality for a population/process); show that the variation of the sample average rapidly decreases as the sample size increases.Tue, 23 Jan 2007 12:42:06 -0500Song: Means Will Follow You
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1624A song describing how sample means will follow the normal curve regardless of how skewed the population histogram is, provided n is very large.Tue, 28 Nov 2006 08:10:09 -0500Standard Errors and The Central Limit Theorm
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1563This lesson introduces the Central Limit Theorem and discusses it in terms of the normal distribution, binomial distribution, and Poisson distribution. Thu, 31 Aug 2006 02:09:33 -0400Sampling Distribution Simulation
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1454This applet demonstrates the Central Limit Theorem. First, select a distribution (Normal, Uniform, Skewed, Custom) and add or delete data points by clicking on the graph. Then, sample from the parent population and the distribution of the sample mean is shown. Users can also choose to see the distribution of the median, standard deviation, variance, and range.Tue, 1 Aug 2006 02:34:40 -0400Additional SOCR Resources
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1448This page provides links to distribution calculators, conceptual demonstration applets, statistical tables, online data analysis packages, function and image-processing tools, and other online computing resources. Key Words: Binomial; Normal; Exponential; Chi-Square; Geometric; Hypergeometric; Negative Binomial; Poisson; Student's T; F-Distribution; Wilcoxon Rank-Sum; Central Limit Theorem; Regression; Normal Approximation to Poisson; Confidence Intervals; Hypothesis Tests; Power; Sample-Size; ANOVA; Galton's Board; Function Plots; Edge Detection; Image Warping & Stretching; Polynomial Model Fitting; Wilcoxon-Mann-Whitney Statistic. Tue, 1 Aug 2006 11:37:00 -0400Free Software
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1395This collection of macros for Microsoft Excel addresses numerous topics like decision trees, the Central Limit Theorem, queueing, critical path analysis, regression with prediction intervals, and recognizing departures from normality.Thu, 13 Jul 2006 03:24:38 -0400Year 13 Statistics Workshop
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=895This page is a resource for a series of workshops held by the Department of Statistics at the University of Auckland (New Zealand). The page contains links to worksheets, applets, and articles on such topics as regression, time series, the central limit theorem, and dice experiments.Tue, 9 Aug 2005 01:11:24 -0400Central Limit Theorem
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=921The program CenLimit shows the effects of the central limit theorem. The user may select from various distributions to draw different numbers of observations for calculating the means. The distribution of the means is plotted. You may use this program to find out the relationship between the number of observations and the resulting standard deviation of the means. Tue, 9 Aug 2005 01:06:25 -0400**Central Limit Theorem Applet
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=1031This applet demonstrates the central limit theorem using simulated dice-rolling experiments. This experiment is performed repeatedly and outcomes are recorded and plotted in the form of a histogram. An article describing this applet and an alternate source for the applet can be found at http://www.amstat.org/publications/jse/v6n3/applets/clt.html.Wed, 22 Jun 2005 02:31:18 -0400**The Central Limit Theorem – How to Tame Wild Populations
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=967Using 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.Mon, 23 May 2005 02:13:09 -0400Sample Means
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=419This site gives an explanation of, a definition for and an example of sample means. Topics include mean, variance, distribution, and the Central Limit Theorem.Tue, 17 May 2005 05:13:01 -0400Simulations and Demonstrations
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=622This is a collection of applets organized by subject of study and searchable. It contains applets for ANOVA, Binomial Distribution, Central Limit Theorem, Chi Square, Confidence Interval, Correlation, Central Tendency, Effect Size, Goodness of Fit, Histogram, Normal Distribution, Power, Regression, Repeated Measures, Restriction of Range, Sampling Distribution, Skew, t-test, and Transformations.Thu, 12 May 2005 04:35:02 -0400**Normal Approximation to the Binomial Distribution
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=623This 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.Thu, 12 May 2005 04:31:09 -0400Against All Odds: 18. The Sample Mean and Control Charts
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=616In this free online video program, "the successes of casino owners and the manufacturing industry are used to demonstrate the use of the central limit theorem. One example shows how control charts allow us to effectively monitor random variation in business and industry. Students will learn how to create x-bar charts and the definitions of control limits and out-of-control limits." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 18. The Sample Mean and Control Charts" and click the "VOD" icon at the top-right of the description.Thu, 12 May 2005 12:34:04 -0400Star Library: Sampling Distributions of the Sample Mean and Sample Proportion
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=886In these activities designed to introduce sampling distributions and the Central Limit Theorem, students generate several small samples and note patterns in the distributions of the means and proportions that they themselves calculate from these samples. Outside of class, students generate samples of dice rolls and coin spins and draw random samples from small populations for which data is given on each individual. Students report their sample means and proportions to the instructor who then compiles the results into a single data file for in-class exploration of sampling distributions and the Central Limit Theorem. Key words: Sampling distribution, sample mean, sample proportion, central limit theorem Thu, 12 May 2005 11:20:31 -0400Communicating With Data
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=804This course features slide shows for each lecture and exams with solutions to teach students how to be intelligent users of management science techniques. The fundamental concepts underlying the quantitative techniques are presented as a way of thinking, not just a way of calculating, in order to enhance decision-making skills. Exercises and examples are drawn from marketing, finance, operations management, strategy, and other management functions. Tue, 10 May 2005 10:26:24 -0400Statistical Applets: Central Limit Theorem Binomial
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=565This applet is designed to help students visualize the effect of the change in sample size on the binomial distribution for any probability of success. This applet accompanies “Practice of Business Statistics;” however, it can be used without this text.Wed, 6 Apr 2005 12:50:15 -0400Statistical Applets: Central Limit Theorem Sample Mean
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http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=564This applet is designed to help students visualize how increasing sample size affects the shape of the sampling distribution of the sample mean. This applet accompanies “Practice of Business Statistics”; however, it can be used without this text.Sat, 12 Mar 2005 09:00:17 -0500Central Limit Theorem
http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=267
http://www.causeweb.org/cwis/index.php?P=FullRecord&ResourceId=267Illustrates the central limit theorem by allowing the user to increase the number of samples in increments of 100, 1000, or 10000.Fri, 24 Sep 2004 04:58:23 -0400