Resource Library

This free online video program "discusses binomial distribution and the criteria for it, and describes a simple way to calculate its mean and standard deviation. An additional feature describes the quincunx, a randomizing device at the Boston Museum of Science, and explains how it represents the binomial distribution."

This free online video program, "demonstrates how to determine the probability of any number of independent events, incorporating many of the same concepts used in previous programs. An interview with a statistician who helped to investigate the space shuttle accident shows how probability can be used to estimate the reliability of equipment."

In this free online video program, "students will learn the distinction between deterministic phenomena and random sampling. This program introduces the concepts of sample space, events, and outcomes, and demonstrates how to use them to create a probability model. A discussion of statistician Persi Diaconis's work with probability theory covers many of the central ideas about randomness and probability."

In this free online video program, students will learn that "statistics can be used to evaluate anecdotal evidence. This program distinguishes between observational studies and experiments and reviews basic principles of design including comparison, randomization, and replication. Case material from the Physician's Health Study on heart disease demonstrates the advantages of a double-blind experiment."

In this free online video program, students will learn that "causation is only one of many possible explanations for an observed association. This program defines the concepts of common response and confounding, explains the use of two-way tables of percents to calculate marginal distribution, uses a segmented bar to show how to visually compare sets of conditional distributions, and presents a case of Simpson's Paradox. The relationship between smoking and lung cancer provides a clear example."

In this free online video program, "students will learn to derive and interpret the correlation coefficient using the relationship between a baseball player's salary and his home run statistics." The students will then "discover how to use the square of the correlation coefficient to measure the strength and direction of a relationship between two variables. A study comparing identical twins raised together and apart illustrates the concept of correlation."

This free online video program offers topics that "include linear growth, least squares, exponential growth, and straightening an exponential growth curve by logic. A study of growth problems in children serves to illustrate the use of the logarithm function to transform an exponential pattern into a line. The program also discusses growth in world oil production over time." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 7. Models for Growth" and click the "VOD" icon at the top-right of the description.

In this free online video program, "students will advance from histograms through smooth curves to normal curves, and finally to a single normal curve for standardized measurement, as this program shows ways to describe the shape of a distribution using progressively simpler methods. In a lesson on creating a density curve, students also learn why, under steadily decreasing deviation, today's baseball players are less likely to achieve a .400 batting average." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 4. Normal Distributions" and click the "VOD" icon at the top-right of the description.

This free online video program uses historical anecdotes and contemporary applications to introduce the series which "explores the vital links between statistics and our everyday world. The program also covers the evolution of the discipline."

This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their dataset. The primary learning goals are to teach students 1) how to obtain a random sample; 2) how to interpret confidence intervals; 3) how to simulate and interpret a sampling distribution; and 4) how to communicate descriptive statistics.