Sorry, you need to enable JavaScript to visit this website.

Laws of Large Numbers

  • 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.
    0
    No votes yet
  • 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.
    0
    No votes yet
  • This webpage provides instructions for teaching p-values and standard distributions using Sampling SIM software. It includes information regarding prerequisite knowledge, common misconceptions, and objectives, as well as links to an activity and a pre/post-test.
    0
    No votes yet
  • This journal article gives examples of erroneous beliefs about probability. It specifically examines the belief that a random sample must be representative of the true population.
    0
    No votes yet
  • This page contains course notes and homework assignments with solutions for a mathematical statistics class. The course covers statistical inference, probability, and estimation principles.
    0
    No votes yet
  • These slides address point estimation including unbiasedness and efficiency and the Cramer-Rao lower bound.
    0
    No votes yet
  • This page discusses the theory behind the bootstrap. It discusses the empirical distribution function as an approximation of the distribution function. It also introduces the parametric bootstrap.
    0
    No votes yet
  • This site provides links to lecture outlines for an upper-level statistics class. Topics include hypothesis testing, ANOVA and regression.
    0
    No votes yet
  • This page will perform basic multiple regression analysis for the case where there are several independent predictor variables, X1, X2, etc., and one dependent or criterion variable, Y. Requires import of data from a spreadsheet.

    0
    No votes yet
  • Part of an online statistics textbook. Topics include: (1) Law of Large Numbers for Discrete Random Variables, (2) Chebyshev Inequality, (3) Law of Averages, (4) Law of Large Numbers for Continuous Random Variables, (5) Monte Carlo Method. There are several examples and exercises that accompany the material.
    0
    No votes yet

Pages