A Galton board is a vertical board with n rows of pegs onto which a ball is dropped. Each time a ball hits a peg, it has a probability p of bouncing to the left and a probability of 1-p of bouncing to the right. The simulation's histogram shows the distribution of x-coordinates as the balls leave the board and are collected into bins. The simulation gives rise to the binomial distribution if the probabilities of left and right bounces are equal. At first there does not seem to be any pattern but after many trials the familiar "bell curve" shape begins to emerge.
This two-part activity provides an introduction to the basics of measurement (linear, mass, volume, density) and discusses the role of inferential statistics in comparing any two measurements. The concept of random variations in measurements is introduced.
Subject:
Mathematics and Statistics, Science and Technology
The EJS Multiple Coin Toss model displays the result of the flipping of N coins. The result of each set of coin flips is shown by the image of the pennies on the screen and the complete results of the tossing experiment is shown on a graph of the cumulative probability of heads. The number of coins flipped, N, and change the "fairness" of the coin by setting the probability of a "heads" result, p, can be set via text boxes.
Subject:
Mathematics and Statistics, Science and Technology
Play Plinko and develop your knowledge of statistics. Drops balls through a triangular grid of pegs and see the balls random walk through the lattice. Watch the histogram of final positions build up and approach the binomial distribution. Inspired by the Virtual Lab in Probability and Statistics at U. Alabama in Huntsville (www.math.uah.edu/stat)
Subject:
Mathematics and Statistics, Science and Technology
This course develops logical, empirically based arguments using statistical techniques and analytic methods. It covers elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation. Emphasis is placed on the use and limitations of analytical techniques in planning practice. This course is required for and restricted to first-year M.C.P. students.
Descriptive and inferential statistics for the behavioral and neurological sciences are considered. Techniques such as t-tests, factorial analysis of (co)variance, correlation, multiple regression, and nonparametric tests are introduced. Subject provides an introductory overview of some advanced methods such as path analysis, factor analysis, discriminant analysis, and analysis of functional MRI data. Basic issues of research design and methodology intimately associated with data analysis are discussed.
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