The Effects of Ethyl Alcohol on a Driver's Driving Skill, Visual Perception, Risk Acceptance, Choice Reaction Times and Information Processing Rates

1974 ◽  
Vol 18 (2) ◽  
pp. 116-116
Author(s):  
Helmut T. Zwahlen
Keyword(s):  
Information Processing ◽  
Standard Deviation ◽  
Visual Perception ◽  
Reaction Times ◽  
Driving Skill ◽  
Alcohol Condition ◽  
The Mean ◽  
Risk Acceptance ◽  
Standard Deviations ◽  
Choice Reaction Times

Twelve subjects (20–37 years old) were tested in the laboratory and eleven out of these were also tested in a car in the field, first under a no alcohol condition and then under an alcohol condition (approximately 0.10% BAC). In the laboratory the subjects simple and choice reaction times for two uncertainty modes were measured and their information processing rates (3 bits unsertainty) were determined. In the field the subjects driving skill for driving through a gap with 20 inches total clearance at 20 MPH was measured, as well as their static visual perceptual capabilities and risk acceptance decisions for a 46 feet viewing distance using psychophysical experimental methods. Based upon the driving skill measure (standard deviation of centerline deviations in the gap), the mean of the psychometric visual gap perception function and the mean of the psychometric gap risk acceptance function, the “Safety Distance” and the “Driver Safety Index” (DSI) were obtained. Based upon a statistical analysis of the data we may conclude first that the effects of alcohol (approximately 0.10% BAC) vary widely from one subject to another (slighthly improved performance to highly impaired performance) and that the changes in the group averages of the means and standard deviations of the psychometric visual perception and risk acceptance functions, the driving skill distributions, the “Safety Distances” and the DSI's for the subjects (although all changes in the group averages are in the expected direction) are statistically not significant (α = .05). Second, the group average of the means of the choice reaction times for the subjects increased by 5% under the alcohol condition (statistically significant, α = .05), but more important the group average of the standard deviations of the choice reaction times for the subjects increased by 23% (statistically significant, α = .05). The group average of the information processing rates for the subjects decreased by 3% (statistically not significant, α = .05) under the alcohol condition. A system model in which the system demands on the driver are represented in terms of choice reaction times is used to demonstrate that the increase in performance variability (expressed by the standard deviation of choice reaction times) under the influence of alcohol provides a much better explanation for the higher accident involvement than the historically most frequently used rather small increase in average performance (expressed by the mean of choice reaction times).

Legibility Study of Selected Scale Characteristics for Moving-Tape Instruments

1965 ◽  
Vol 7 (6) ◽  
pp. 545-555 ◽  
Author(s):  
Barbara J. Kelso
Keyword(s):  
Air Force ◽  
Reaction Times ◽  
Scale Factor ◽  
Verbal Response ◽  
Scale Factors ◽  
Scale Characteristics ◽  
The Mean ◽  
Standard Deviations ◽  
Vertical Scales ◽  
Speed And Accuracy

A legibility study was performed to investigate the effects of scale factors, graduation marks, orientation of scales, and reading conditions on the speed and accuracy of reading moving-tape instruments. Each of 150 Air Force Officers made 150 self-paced readings from slides of hand drawn tape instruments. Error was expressed as the magnitude of deviation of a subjects' verbal response from the set scale value. An analysis of variance was performed on the mean error scores, standard deviations of error, mean reaction times, and standard deviations of reaction times. The results clearly favored the 1 7/8 inch scale factor over the 1 3/8 inch and the 2 3/8 scale factor. The use of 9 graduation marks was superior to either 0, 1, 3, or 4 graduation marks. Reading conditions had little effect on performance. Horizontal scales were read more rapidly but no more accurately than vertical scales.

A Proof for Rhiel's Range Estimator of the Coefficient of Variation for Skewed Distributions

2007 ◽  
Vol 100 (1) ◽  
pp. 208-210 ◽  
Author(s):  
G. Steven Rhiel
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Research Study ◽  
Skewed Distributions ◽  
The Mean ◽  
Standard Deviations

In this research study is proof that the coefficient of variation ( CVhigh-low) calculated from the highest and lowest values in a set of data is applicable to specific skewed distributions with varying means and standard deviations. Earlier Rhiel provided values for dn, the standardized mean range, and an, an adjustment for bias in the range estimator of μ. These values are used in estimating the coefficient of variation from the range for skewed distributions. The dn and an values were specified for specific skewed distributions with a fixed mean and standard deviation. In this proof it is shown that the dn and an values are applicable for the specific skewed distributions when the mean and standard deviation can take on differing values. This will give the researcher confidence in using this statistic for skewed distributions regardless of the mean and standard deviation.

Alum Production from some Nigerian Kaolinite Deposits

2012 ◽  
Vol 7 ◽  
pp. 13-19 ◽  
Author(s):  
L.C. Edomwonyi-Otu ◽  
B.O. Aderemi ◽  
O. Edomwonyi-Otu ◽  
A. Simo ◽  
M. Maaza
Keyword(s):  
Standard Deviation ◽  
Surface Area ◽  
Science And Technology ◽  
Mineral Resources ◽  
Kaolinite Clay ◽  
Processing Technologies ◽  
Commercial Alumina ◽  
Bet Analysis ◽  
The Mean ◽  
Standard Deviations

The Development of Sustainable Processing Technologies for the Vast Mineral Resources Available in Nigeria and their Varied Applications Is a Major Pursuit by the Federal Ministry of Science and Technology. in this Work, Alum Was Produced from Three Different Kaolin Deposits in Nigeria Namely Kankara Brown, Bauchi and Kankara White by Acid Dealumination of the Metakaolin Obtained by Calcination of the Beneficiated Kaolinites and the Yields Were Measured to Ascertain the Process Repeatability. the Reproducibility Studies Carried Out on Samples from each Deposit Showed a Mean Yield of 80 %, 92 % and 87 % and Standard Deviation of 2.50 %, 1.063 % and 1.296 %, for Kankara Brown, Bauchi and Kankara White Respectively. the Values from the Three Deposits Fall within 3 Standard Deviations of the Mean in Accordance with the 68-95-99.7/three-Sigma Rule. the Alum Quality Also Compares Well with Available Commercial Alums in the Market. BET Analysis, of the Alumina Obtained by Calcination of the Alum (Kankara White), Gave a Surface Area of 192.2441m2/g Comparable to Commercial Alumina. these Results Suggest/establishes the Huge Possibility of Commercial Alum Production, Including Alumina, Using Kaolinite Clay from these Deposits as Starting Materials.

scholarly journals The GRIMMER test: A method for testing the validity of reported measures of variability

2016 ◽  
Author(s):  
Jordan Anaya
Keyword(s):  
Standard Deviation ◽  
Sample Size ◽  
Standard Error ◽  
Standard Errors ◽  
Rounding Error ◽  
Small Variance ◽  
The Mean ◽  
Standard Deviations ◽  
Mathematical Foundations ◽  
Repetitive Pattern

GRIMMER (Granularity-Related Inconsistency of Means Mapped to Error Repeats) builds upon the GRIM test and allows for testing whether reported measures of variability are mathematically possible. GRIMMER relies upon the statistical phenomenon that variances display a simple repetitive pattern when the data is discrete, i.e. granular. This observation allows for the generation of an algorithm that can quickly identify whether a reported statistic of any size or precision is consistent with the stated sample size and granularity. My implementation of the test is available at PrePubMed (http://www.prepubmed.org/grimmer) and currently allows for testing variances, standard deviations, and standard errors for integer data. It is possible to extend the test to other measures of variability such as deviation from the mean, or apply the test to non-integer data such as data reported to halves or tenths. The ability of the test to identify inconsistent statistics relies upon four factors: (1) the sample size; (2) the granularity of the data; (3) the precision (number of decimals) of the reported statistic; and (4) the size of the standard deviation or standard error (but not the variance). The test is most powerful when the sample size is small, the granularity is large, the statistic is reported to a large number of decimal places, and the standard deviation or standard error is small (variance is immune to size considerations). This test has important implications for any field that routinely reports statistics for granular data to at least two decimal places because it can help identify errors in publications, and should be used by journals during their initial screen of new submissions. The errors detected can be the result of anything from something as innocent as a typo or rounding error to large statistical mistakes or unfortunately even fraud. In this report I describe the mathematical foundations of the GRIMMER test and the algorithm I use to implement it.

Adaptation of an Alkaline Phosphatase Method for Automatic Colorimetric Analysis

1959 ◽  
Vol 5 (2) ◽  
pp. 119-126 ◽  
Author(s):  
Walton H Marsh ◽  
Benjamin Fingerhut ◽  
Elaine Kirsch
Keyword(s):  
Alkaline Phosphatase ◽  
Enzyme Activity ◽  
Standard Deviation ◽  
Enzyme Concentration ◽  
Mean Value ◽  
Colorimetric Analysis ◽  
Manual Method ◽  
Automated Method ◽  
The Mean ◽  
Standard Deviations

Abstract The alkaline phosphatase method of Kind and King was adapted to an automated recording colorimeter. The precision of the automated method (1 standard deviation as per cent of the mean value) was ±1.7 and for the manual method ±3.6 per cent. The color produced was proportional to the enzyme concentration by both methods, and recoveries of added phenol were satisfactory. In more than 150 serum specimens surveyed for enzyme activity, over 95 per cent of the results (2 standard deviations) of the 2 methods in the range 3.4-129 agree to within ±2.8 King-Armstrong units/1OO ml.

Statistics of spontaneous electrical activity of supra- and ectosylvian gyri of the dog

1963 ◽  
Vol 204 (1) ◽  
pp. 51-59
Author(s):  
Archie R. Tunturi
Keyword(s):  
Standard Deviation ◽  
Electrical Activity ◽  
Negative Correlation ◽  
Evoked Potential ◽  
Correlation Coefficients ◽  
Moderate Correlation ◽  
Spontaneous Electrical Activity ◽  
Suprasylvian Gyrus ◽  
The Mean ◽  
Standard Deviations

The standard deviations of the spontaneous electrical activity (SEA) of the suprasylvian gyrus (SSG) ranged between 57–131 µv and for the middle ectosylvian (MES) gyrus, 88–175 µv. Correlation coefficients, r, served to distinguish three regions of the SSG. The rostral showed low correlation with the middle, high correlation with the caudal, and low to negative correlation with the MES. The middle showed moderate correlation with the MES, and the caudal showed zero to negative correlation with the MES. Within the SSG, correlation was low and in the MES high, for spacings of 2 mm. Cocaine applied to both areas sharpened the boundaries at the sulci, reduced standard deviations, did not affect the correlation between the caudal SSG and the MES area, and increased r between all locations in the MES but not in the SSG. Cocaine on the SSG had no effect on the mean and standard deviation of the evoked potential in the MES, but decreased r of the SEA significantly.

scholarly journals On the Formulation and Universality of Monin–Obukhov Similarity Functions for Mean Gradients and Standard Deviations in the Unstable Surface Layer: Results from Surface-Layer-Resolving Large-Eddy Simulations

2017 ◽  
Vol 74 (4) ◽  
pp. 989-1010 ◽  
Author(s):  
Björn Maronga ◽  
Joachim Reuder
Keyword(s):  
Surface Layer ◽  
Standard Deviation ◽  
Large Eddy Simulations ◽  
Specific Humidity ◽  
Horizontal Wind ◽  
Convective Conditions ◽  
Similarity Functions ◽  
Large Eddy ◽  
The Mean ◽  
Standard Deviations

Abstract Surface-layer-resolving large-eddy simulations (LESs) of free-convective to near-neutral boundary layers are used to study Monin–Obukhov similarity theory (MOST) functions. The LES dataset, previously used for the analysis of MOST relationships for structure parameters, is extended for the mean vertical gradients and standard deviations of potential temperature, specific humidity, and wind. Also, local-free-convection (LFC) similarity is studied. The LES data suggest that the MOST functions for mean gradients are universal and unique. The data for the mean gradient of the horizontal wind display significant scatter, while the gradients of temperature and humidity vary considerably less. The LES results suggest that this scatter is mostly related to a transition from MOST to LFC scaling when approaching free-convective conditions and that it is associated with a change of the slope of the similarity functions toward the expected value from LFC scaling. Overall, the data show slightly, but consistent, steeper slopes of the similarity functions than suggested in literature. The MOST functions for standard deviations appear to be unique and universal when the entrainment from the free atmosphere into the boundary layer is sufficiently small. If entrainment becomes significant, however, we find that the standard deviation of humidity no longer follows MOST. Under free-convective conditions, the similarity functions should reduce to universal constants (LFC scaling). This is supported by the LES data, showing only little scatter, but displaying a systematic height dependence of these constants. Like for MOST, the LFC similarity constant for the standard deviation of specific humidity becomes nonuniversal when the entrainment of dry air reaches significant levels.

Cardiac Deceleration and Accuracy of Performance: Recalculation of Standard Score Transform

1979 ◽  
Vol 49 (1) ◽  
pp. 297-298
Author(s):  
Nicholas John Carriero
Keyword(s):  
Standard Deviation ◽  
Standard Score ◽  
Raw Data ◽  
Cardiac Deceleration ◽  
The Mean ◽  
Standard Deviations

In two previous studies the standard score transform used was based on a standard deviation derived from the mean standard deviations of the raw data in the six classifications employed in the studies rather than on one based on the entire set of raw scores as is the more common practice. The data were reanalyzed using the latter basis and major findings were confirmed. Some of the minor findings, however, were changed. These changes are pointed out and discussed where they occurred.

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