Poses the following problem: Suppose there was one of six prizes inside your favorite box of cereal. Perhaps it's a pen, a plastic movie character, or a picture card. How many boxes of cereal would you expect to have to buy, to get all six prizes?
Poses the following problem: Suppose there was one of six prizes inside your favorite box of cereal. Perhaps it's a pen, a plastic movie character, or a picture card. How many boxes of cereal would you expect to have to buy, to get all six prizes?
This site offers separate webpages about statistical topics relevant to those studying psychology such as research design, representing data with graphs, hypothesis testing, and many more elementary statistics concepts. Homework problems are provided for each section.
Approximating a normal distribution with a binomial distribution
This page supports an in-class exercise that highlights several key Bayesian concepts. The scenario is as follows: a large paper bag contains pieces of candy with wrappings of different color, and we are interested in learning about the unknown proportion of yellow-wrapped pieces of candy. After completing the exercises, we will be familiar with the following concepts and ideas: probability distributions can quantify degree of belief, prior distribution, posterior distribution, sequential updating, conjugacy, Cromwell’s Rule (http://en.wikipedia.org/wiki/Cromwell's_rule), the data overwhelm the prior, Bayes factors, Savage-Dickey density ratio, sensitivity analysis, coherence.
This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.
An important idea in statistics is that the amount of data matters. We often teach this with formulas --- the standard error of the mean, the t-statistic, etc. --- in which the sample size appears in a denominator as √n. This is fine, so far as it goes, but it often fails to connect with a student's intuition. In this presentation, I'll describe a kinesthetic learning activity --- literally a random walk --- that helps drive home to students why more data is better and why the square-root arises naturally and can be understood by simple geometry. Students remember this activity and its lesson long after they have forgotten the formulas from their statistics class.
This applet displays various distributions and allows the user to experiment with the parameters to see the effects on the curve.
This applet simulates rolling dice to illustrate the central limit theorem. The user can choose between 1, 2, 6, or 9 dice to roll 1, 5, 20, or 100 times. The distribution is graphically displayed. This applet needs to be resized for optimal viewing.
This applet shades the graph and computes the probability of X, when X is between two parameters x1 and x2. The user inputs the mean, standard deviation, x1 and x2. This applet should be resized for optimal viewing.
This applet shows the normal or Gaussian distribution. The distribution has two parameters, the mean and the standard deviation. Click the draw button after filling in new values for the mean and the standard deviation to obtain a new diagram of the normal distribution.