A cosine approximation to the normal distribution

A cosine function is suggested to approximate the normal distribution as a device for simplifying algebraic manipulations of the latter. Numerical evaluations remain straightforward and employ only the commonly available trigonometric tables. A method of visual curve fitting requiring only an oscilloscope is also described.     

The mean and standard deviation of the distribution of group assembly sums

An interesting problem in linear programming is the group assembly problem which is mathematically equivalent to the general transportation problem of economics. Computer programs designed for the determination of exact and approximate optimal group assemblies have been available for some time. This paper presents formulas for the mean and squared standard deviation of the distribution of all possible group assembly sums. Computational techniques are presented and the results are related to those of the analysis of variance of ak-factor problem withn levels of each factor.This research was supported in part by the United States Air Force under Project No. 7713, Task No. 77232, and Contract No. AF 18(600)-1050, monitored by the Crew Research Laboratory of the Air Force Personnel and Training Research Center. Permission is granted for reproduction, translation, publication, use, and disposal in whole and in part by or for the United States Government.     

Analysis of mean learning of normal participants on the Rey Auditory-Verbal Learning Test

Analysis of the mean performance of 58 groups of normal adults and children on the free-recall trials of the Rey Auditory-Verbal Learning Test shows that the mean auditory-verbal learning of each group is described by the function R1 + Sln(t), where R1 is a measure of the mean immediate memory span, S is the slope of the mean logarithmic learning curve, and ln(t) is the natural logarithm of the trial number t. The analysis also shows that R1 varies with age and other demographic factors, whereas S is almost a constant, and it yields equations for estimating the effect of these factors on R1. Potential use of these findings for assessment of auditory-verbal memory and learning in comparative clinical studies is discussed.     

An abac for determining the mean deviation of a class from the general mean

The abac is presented with instructions for use.     

Wide distribution of external local sign in the normal population

The extent of the apparent visual field was determined for a group of 78 naïve visual observers. We find that there exists a minority (less than 10%) that is essentially veridical, but that the majority of the population experiences an apparent visual field of only about 90°, thus much narrower than the dioptrics of the eye would suggest (a little over 180°). This is in good accordance with available (albeit mainly anecdotal) evidence, though formal data have been lacking thus far. The finding is discussed in the context of metrical calibration of the topological structure of the visual field, an aspect of “local sign”.     

On the relation between the mean and the variance of a diffusion model response time distribution

Almost every empirical psychological study finds that the variance of a response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion model (e.g., Ratcliff (1978) Psychological Review, 85, 59-108; Ratcliff (2002). Psychonomic Bulletin & Review, 9, 278-291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion model RT distribution. Next, we study how systematic differences in two important diffusion model parameters simultaneously affect the mean and the variance of the diffusion model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.     

Confidence intervals and sample size calculations for the standardized mean difference effect size between two normal populations under heteroscedasticity

The use of effect sizes and associated confidence intervals in all empirical research has been strongly emphasized by journal publication guidelines. To help advance theory and practice in the social sciences, this article describes an improved procedure for constructing confidence intervals of the standardized mean difference effect size between two independent normal populations with unknown and possibly unequal variances. The presented approach has advantages over the existing formula in both theoretical justification and computational simplicity. In addition, simulation results show that the suggested one- and two-sided confidence intervals are more accurate in achieving the nominal coverage probability. The proposed estimation method provides a feasible alternative to the most commonly used measure of Cohen’s d and the corresponding interval procedure when the assumption of homogeneous variances is not tenable. To further improve the potential applicability of the suggested methodology, the sample size procedures for precise interval estimation of the standardized mean difference are also delineated. The desired precision of a confidence interval is assessed with respect to the control of expected width and to the assurance probability of interval width within a designated value. Supplementary computer programs are developed to aid in the usefulness and implementation of the introduced techniques.     

The nontruncated marginal of a truncated bivariate normal distribution

Inference is considered for the marginal distribution ofX, when (X, Y) has a truncated bivariate normal distribution. TheY variable is truncated, but only theX values are observed. The relationship of this distribution to Azzalini's skew-normal distribution is obtained. Method of moments and maximum likelihood estimation are compared for the three-parameter Azzalini distribution. Samples that are uniformative about the skewness of this distribution may occur, even for largen. Profile likelihood methods are employed to describe the uncertainty involved in parameter estimation. A sample of 87 Otis test scores is shown to be well-described by this model.     

Estimation of parameters in a truncated trivariate normal distribution

This paper gives maximum-likelihood estimators for certain parameters in a truncated trivariate normal distribution when the values of the other parameters are known. The estimators are functions of a random sample. Approximate variances and covariances of the estimators, when the sample size is large, are also given. The type of truncation considered is merely restriction of the range of one of the variates, whose true mean and variance are assumed to be known. Two cases of such restriction are treated: (a) ( x < + ); (b) (- <x '), where and ' are arbitrary cutoff points which are assumed to be known. A precise statement of the estimation problem is given in Section 1. Section 2 contains preliminary calculations. The estimators appear in Section 3. The asymptotic variances and covariances of the estimators are given in Section 4. The estimators and their asymptotic variances and covariances can be easily specialized to be suitable for the case of a certain truncated bivariate normal distribution (Sections 3 and 4).