This article offers some less-than-rigorous explanations for the notion of degrees of freedom, and for the particular formulae to be used when computing those values.

This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…

Descripting Statistics provides methodology and tools for user-friendly presentation of random data. Among the summary measures that describe focal tendencies in random data, the mode is given the least amount of attention and it is frequently misinterpreted in many introductory textbooks on statistics. The purpose of the paper is to provide a…

The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…

The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…

The online deployment of Technology Engineered online Student Ratings of Instruction (SRIs) by colleges and universities in the United States has dynamically changed the deployment of course evaluation. This research investigation is the fourth part of a post hoc study that analytically and psychometrically examines the design, reliability, and…

A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

The normalized mean is developed and discussed as a descriptive measure of central location. The advantages of the normalized mean over the arithmetic mean, median, and trimmed mean are discussed. (Author)

Introduces a new iteration model for the calculation of co-word maps. Co-word analysis is an objective quantitative method for analyzing and integrating survey information about research trends and structures that avoids problems using statistical methods to produce mappings of reduced information. (PEN)

Studies binomial, negative binomial, and gamma regression models and gives a detailed description of inference procedures based on them. The process of model fitting and evaluation is illustrated by examples referring to the determination of endpoints in acute and chronic toxicity tests. (17 references) (Author/MDH)

The problem of monitoring trends for changes at unknown times is considered. Statistics that permit one to focus high power on a segment of the monitored period are studied. Numerical procedures are developed to compute the null distribution of these statistics. (Author)

Presents results of an investigation of a formula for rank correlation. The exploration turned up an unexpected connection and showed the formula to be far from arbitrary. (PK)

Describes two simple methods of error analysis: (1) combining errors in the measured quantities; and (2) calculating the error or uncertainty in the slope of a straight-line graph. Discusses significance of the error in the comparison of experimental results with some known value. (MDH)