Resource Library

Advanced Search | Displaying 751 - 760 of 1111
  • 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.
    0
    No votes yet
  • Joke from "The Little Black Book of Business Statistics", by Michael C. Thomsett (1990, Amacom) p. 117. also quoted in "Statistically Speaking" compiled by Carl Gaither and Alma Cavazos-Gaither.
    0
    No votes yet
  • Essentially, all models are wrong, but some are useful. This quote is generally attributed to George Box. It appears in "Empirical Model-Building and Response Surfaces" (Wiley 1987) p. 424 by George E.P. Box & Norman R. Draper.
    0
    No votes yet
  • This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups. The simulation then compares the difference in the groups based on this haphazard selection to those of a truly random assignment (the user may also create multiple random assignments and examine the sampling distribution of key statistics). The applet may be used to illustrate three points about random assignment in experiments: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments. Key Note for Instructors: The data are drawn from a real experiment with an effective treatment but where the response is correlated with animal age and size (so tumor size will tend to be smaller in the treatment group when measured at the end of a randomized experiment but animal age and size should not be). Typically people choosing haphazardly will tend to pick larger/older animals for the treatment group and thus create a bias against the treatment.
    0
    No votes yet
  • A cartoon to use at the end of a class period when the instructor was rushed to finish. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
    1
    Average: 1 (1 vote)
  • This tutorial exposes students to conducting chi-square tests in SPSS. This html based tutorial provides extensive screen shots and an example data set.
    0
    No votes yet
  • This tutorial exposes students to conducting multiple comparisons in SPSS. This html based tutorial provides extensive screen shots and an example data set. Topics covered in the tutorial include one way ANOVA, preplanned contrasts, Bonferroni, Post Hoc Tukey's HSD, and Scheffe's multiple contrasts.
    0
    No votes yet
  • This website serves as an online textbook for introductory statistics, covering topics such as summarizing and presenting data, producing data, variation and probability, statistical inference, and control charts.
    0
    No votes yet
  • This introductory probability textbook, freely available here in pdf format, emphasizes the use of computing to simulate experiments and make computations. A set of programs that go with the book and the answers to the odd-numbered problems are also available from this site. Chapter headings include: Discrete Probability, Continuous Probability Densities, Combinatorics, Conditional Probability, Distributions and Densities, Expected Value and Variance, Sums of Random Variables, Law of Large Numbers, Central Limit Theorem, Generating Functions, Markov Chains, and Random Walks.
    0
    No votes yet
  • This tutorial presentation from INFORMS Applied Probability Society covers the long range dependence (or long memory)property of certain stationary stochastic processes.
    0
    No votes yet

Pages

register