Statistical Inference & Techniques

  • This applet simulates rolling dice and displays the outcomes in a histogram. Students can choose to roll 1, 2, 6, or 9 dice either 1, 10, 20, or 100 times. The outcome studied is the sum of the dice and a red line is drawn on the histogram to show expected number of occurences of each outcome.

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  • This section of the Engineering Statistics Handbook gives the normal probability density function as well as the standard normal distribution equations. Example graphs of the distributions are shown and a justification of the Central Limit Theorem is included.
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  • This simulation applet shows groups of confidence intervals for a given alpha based on a standard normal distribution. It shows how changes in alpha affect the proportion of confidence intervals that contain the mean. An article and an alternative source for this applet can be found at http://www.amstat.org/publications/jse/v6n3/applets/confidenceinterval.html.
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  • This applet allows you to explore the validity of confidence intervals on a proportion with various values for sample size (N) and population proportion (Pi). After you specify N, Pi, the level of confidence, and the number of simulations you wish to perform, the applet samples data according to your specification and computes a confidence interval for each simulation. The proportion of simulations for which the confidence interval contains Pi is recorded. If the method for constructing confidence intervals is valid, then about 95% of the 95% confidence intervals should contain Pi.
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  • A pinch of probability is worth a pound of perhaps. A quote by American humorist and cartoonist James Thurber (1894 - 1961). The quote appeared in "Such a Phrase as Drifts Through Dreams," a short story in Thurber's last book, "Lanterns and Lances", Harper Publishing, 1961. The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.
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  • This goal of this resource is to aid in the understanding of the relationship between statistics and the scientific method and how it applies to psychology and the behavioral sciences. The learner will learn how to read and understand the statistics presented in the professional literature and will learn how to calculate and communicate statistical information to others.
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  • This resource contains a broad range of information concerning statistics. It is divided up into 18 chapters and also includes links to other resources pertaining to statistics.
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  • Use the Sample Size Calculator to determine the sample size you need in order to get results that reflect the target population as precisely as needed. You can also find the level of precision you have in an existing sample. The site also describes terms you need to know to understand confidence intervals and what they mean.

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  • The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform). Users then select one of the distributions and change the sample size to see how the distribution of the sample mean approaches normality. Users can also change the number of samples. To select between the different applets you can click on Statistical Theory, the Central Limit Theorem and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/
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  • This applet simulates and plots the sampling distribution of various statistics (i.e. mean, standard deviation, variance). The applet allows the user to specify the population distribution, sample size, and statistic. An animated sample from the population is shown and the statistic is plotted. This can be repeated to produce the sampling distribution of the statistic. After the sampling distribution is plotted it can be compared to a normal distribution by overlaying a normal curve. These features make it useful for introducing students in a first course to the idea of a sampling distribution. The site also includes instructions and exercises. Also available at: http://www.stat.ucla.edu/~dinov/courses_students.dir/Applets.dir/SamplingDistributionApplet.html
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