This activity uses a computer program to explore probability concepts such as sample space, independent events, law of large numbers, and reliability. An outline of the activity and the computer program are provided.
This activity uses Microsoft Excel for a simulation of probability concepts. The Excel file and handouts are provided. Students will explore the concept of independent events, sample spaces, equally likely probabilities, and percentages within the context of this simulation.
This activity uses Microsoft Excel and a deck of playing cards to gain experience with probability concepts. Students will discuss independent events, sample spaces, equally likely probabilities, probability of the intersection of two independent events, probability of the union of two events, percentages, and complements of given events within the context of these simulations. The Excel file and handouts are provided.
Through this activity students will gain an understanding of the effect of the sample size on experiments and simulations. A Microsoft Excel program file and handouts are provided.
This project examines the randomness of clusters using the Poisson Distribution. Using Microsoft Excel, the activity simulates the bombs of London and examines the occurences per cell to estimate lambda.
This article presents data for examining the ability of individuals to choose numbers randomly. Three datasets of six-tuples selected by a lottery game, generated by S-Plus, and chosen by college students can be compared using descriptive statistics and goodness of fit tests to explore bias and randomness. Key Words: Boxplots; Chi-squared tests; Minimum gap; QQ plots.
The dataset described in this article contains data on retired Major League Baseball players, eligible for the MLB Hall of Fame. The data can be used to illustrate descriptive statistical methods (numerical, graphical, and tabular) or inferential statistics (hypothesis testing, confidence intervals, etc.). The data is in .dat format.
This article describes a dataset containing Major League Baseball data from seasons 1969 through 2000 and illustrates how this data can be used as a course long project covering basic data management, the use of exploratory data analysis to "clean" data, and construction of regression models. The data is in .dat format.
This article describes a dataset on the 2000 National Football League (NFL) regular season and the exploratory data analyses performed. Key Words: Multivariate analysis; Summary ranking measures
The datasets described in this article contain information for all National Football League (NFL)regular season and playoff games played from 1993 to 1996. In addition to game scores, the data give oddsmakers' pointspreads and over/under values for each game. Key Words: Predictions; Wagering.
