Resource Library

This program allows the student to explore the nature of sampling distributions of sample means and sample proportions. The software provides separate windows for building population distributions, drawing and viewing random samples from the population, exploring the behavior of sampling distributions of sample means, and exploring the behavior of confidence intervals.

This probability activity discusses the differences among various kinds of studies and which types of inferences can legitimately be drawn from each, as well as how sample statistics reflect the values of population parameters and use sampling distributions as the basis for informal inference. The procedure and assessment are provided.

This page explores Benford's Law: For naturally occurring data, the digits 1 through 9 do not have equal probability of being the first significant digit in a number; the digit 1 has greater odds of being the first significant digit than the others. This law can be used to catch tax fraud because truly random numbers used by embezzlers do not meet this condition.

This is an example of "growing" a decision tree to analyze two possible outcomes. The tree's branches examine the two possible conditions of employee drug use with corresponding probabilities. This example looks at the final outcome probabilities of being correctly and incorrectly identified versus testing accuracy.

This lesson describes bootstrapping in the context of a statistics class for psychology students.

This article describes an interactive activity illustrating general properties of hypothesis testing and hypothesis tests for proportions. Students generate, collect, and analyze data. Through simulation, students explore hypothesis testing concepts. Concepts illustrated are: interpretation of p-values, type I error rate, type II error rate, power, and the relationship between type I and type II error rates and power. This activity is appropriate for use in an introductory college or high school statistics course. Key words: hypothesis test on a proportion, type I and II errors, power, p-values, simulation

This article describes an interactive activity illustrating sampling distributions for means, properties of confidence intervals, properties of hypothesis testing, confidence intervals for means, and hypothesis tests for means. Students generate and analyze data and through simulation explore these concepts. The activity is completed in three parts. The three parts of the activity can be used in sequence or they can be used individually as "stand alone" activities. This allows the educator flexibility in utilizing the activity. Part I illustrates the sampling distribution of the sample mean. Part II illustrates confidence intervals for the population mean. Part III illustrates hypothesis tests for the population mean. This activity is appropriate for use in an introductory college or high school AP statistics course. Key words: sampling distribution of a sample mean, confidence interval for a mean, hypothesis test on a mean, simulation, random rectangles

This Electronic Statistics Textbook offers training in the understanding and application of statistics ... and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. Quoted from the index page of the text.

This part of the NIST Engineering Statistics Handbook contains case studies for Exploratory Data Analysis. Some of the topics include normal and uniform random numbers, reliability using airplane glass failure times, and analysis of primary factors using ceramic strength.

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.