scholarly journals Catalogue of Clusters that are Members of Superclusters

1983 ◽  
Vol 104 ◽  
pp. 185-186
Author(s):  
M. Kalinkov ◽  
K. Stavrev ◽  
I. Kuneva
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
The Other ◽  
Clusters Of Galaxies ◽  
Number Of Clusters ◽  
Abell Clusters ◽  
The Mean ◽  
Abell Cluster ◽  
Image Position

An attempt is made to establish the membership of Abell clusters in superclusters of galaxies. The relation is used to calibrate the distances to the clusters of galaxies with two redshift estimates. One is m10, the magnitude of the ten-ranked galaxy, and the other is the “mean population,” P, defined by: where p = 40, 65, 105 … galaxies for richness groups 0, 1, 2 …, and r is the apparent radius in degrees given by: The first iteration for redshift, z1, is obtained from m10 alone: The standard deviation for Eq. (1) is 0.105, the number of clusters with known velocities is 342 and the correlation coefficient between observed and fitted values is 0.921. With zi from Eq. (1), we define Cartesian galactic coordinates Xi = Rih−1 cosBi cosLi, Yi = Rih−1 cosBi sinLi, Zi = Rih−1 sinBi for each Abell cluster, i = 1, …, 2712, where Ri is the distance to the cluster (Mpc), and Ho = 100 h km s−1 Mpc−1.

scholarly journals On The Estimation of Means and Variances In The Case Of Unequal Components

1975 ◽  
Vol 8 (3) ◽  
pp. 323-335 ◽  
Author(s):  
Esa Hovinen
Keyword(s):  
Standard Deviation ◽  
The Other ◽  
Insurance Companies ◽  
Loss Ratio ◽  
Weighted Mean ◽  
The Mean ◽  
Image Position ◽  
Statistical Work ◽  
Better Than

In practical statistical work one frequently meets certain problems. For instance, we may have the following data about loss ratios in certain insurance companies and corresponding, numbers of insurance in force:I assume further that we have no reason to believe that the companies, their loss ratios and their structure of insurances in force differ in any other way than by the size of companies. The problem is how to get quick estimates of mean losses and their variances in different companies?A straitforward way to estimate the mean loss ratio would be to compute the usual mean of numbers pi, (Σpi/6) = 14; its standard deviation is 6,5. As this procedure of the “first statistician” seems to be too simple and naive, a “more cautious” statistician would compute the weighted mean loss ratioThe “more cautious” statistician would arque that his result is much better than the other result 14. But what would be the variance of the estimate 7,1, and what is the variance in the different companies?

scholarly journals An alternative to the rejection of observations

1932 ◽  
Vol 137 (831) ◽  
pp. 78-87 ◽  
Keyword(s):  
Standard Deviation ◽  
Continuous Function ◽  
Large Deviations ◽  
Opposite Direction ◽  
Standard Error ◽  
The Other ◽  
Cause Of Error ◽  
The Mean ◽  
Normal Law ◽  
Usual Rule

1. It is widely felt that any method of rejecting observations with large deviations from the mean is open to some suspicion. Suppose that by some criterion, such as Peirce’s and Chauvenet’s, we decide to reject observations with deviations greater than 4 σ, where σ is the standard error, computed from the standard deviation by the usual rule; then we reject an observation deviating by 4·5 σ, and thereby alter the mean by about 4·5 σ/ n , where n is the number of observations, and at the same time we reduce the computed standard error. This may lead to the rejection of another observation deviating from the original mean by less than 4 σ, and if the process is repeated the mean may be shifted so much as to lead to doubt as to whether it is really sufficiently representative of the observations. In many cases, where we suspect that some abnormal cause has affected a fraction of the observations, there is a legitimate doubt as to whether it has affected a particular observation. Suppose that we have 50 observations. Then there is an even chance, according to the normal law, of a deviation exceeding 2·33 σ. But a deviation of 3 σ or more is not impossible, and if we make a mistake in rejecting it the mean of the remainder is not the most probable value. On the other hand, an observation deviating by only 2 σ may be affected by an abnormal cause of error, and then we should err in retaining it, even though no existing rule will instruct us to reject such an observation. It seems clear that the probability that a given observation has been affected by an abnormal cause of error is a continuous function of the deviation; it is never certain or impossible that it has been so affected, and a process that completely rejects certain observations, while retaining with full weight others with comparable deviations, possibly in the opposite direction, is unsatisfactory in principle.

scholarly journals Nature versus Nurture in Shallow Convection

2010 ◽  
Vol 67 (5) ◽  
pp. 1655-1666 ◽  
Author(s):  
David M. Romps ◽  
Zhiming Kuang
Keyword(s):  
Standard Deviation ◽  
The Other ◽  
Cloud Base ◽  
Shallow Convection ◽  
Eddy Simulation ◽  
Cloud Properties ◽  
Nature Versus Nurture ◽  
Large Eddy ◽  
The Mean ◽  
Single Set

Abstract Tracers are used in a large-eddy simulation of shallow convection to show that stochastic entrainment (and not cloud-base properties) determines the fate of convecting parcels. The tracers are used to diagnose the correlations between a parcel’s state above the cloud base and both the parcel’s state at the cloud base and its entrainment history. The correlation with the cloud-base state goes to zero a few hundred meters above the cloud base. On the other hand, correlations between a parcel’s state and its net entrainment are large. Evidence is found that the entrainment events may be described as a stochastic Poisson process. A parcel model is constructed with stochastic entrainment that is able to replicate the mean and standard deviation of cloud properties. Turning off cloud-base variability has little effect on the results, which suggests that stochastic mass-flux models may be initialized with a single set of properties. The success of the stochastic parcel model suggests that it holds promise as the framework for a convective parameterization.

Rapid Rhino versus Merocel nasal packs in septal surgery

2011 ◽  
Vol 125 (12) ◽  
pp. 1244-1246 ◽  
Author(s):  
A Hesham ◽  
A Ghali
Keyword(s):  
Standard Deviation ◽  
Pain Score ◽  
Visual Analogue Score ◽  
Nasal Packing ◽  
The Other ◽  
Septal Surgery ◽  
Patient Tolerance ◽  
Operative Complications ◽  
The Mean

AbstractObjective:To compare Rapid Rhino and Merocel packs for nasal packing after septoplasty, in terms of patient tolerance (both with the pack in place and during removal) and post-operative complications.Materials and methods:Thirty patients (aged 18–40 years) scheduled for septoplasty were included. Following surgery, one nasal cavity was packed with Rapid Rhino and the other one with Merocel. Patients were asked to record pain levels on a visual analogue score, on both sides, with the packs in situ and during their removal the next day. After pack removal, bleeding was compared on both sides.Results:The mean ± standard deviation pain score for the Rapid Rhino pack in situ (4.17 ± 1.78) was less than that for the Merocel pack (4.73 ± 2.05), but not significantly so (p = 0.314). The mean pain score for Rapid Rhino pack removal (4.13 ± 1.76) was significantly less that that for Merocel (6.90 ± 1.67; p = 0.001). Bleeding after pack removal was significantly less for the Rapid Rhino sides compared with the Merocel sides (p <0.05).Conclusion:Rapid Rhino nasal packs are less painful and cause less bleeding, compared with Merocel packs, with no side effects. Thus, their use for nasal packing after septal surgery is recommended.

scholarly journals Nadir Correction of AIRS Radiances

2010 ◽  
Vol 27 (3) ◽  
pp. 470-480 ◽  
Author(s):  
Chee-Kiat Teo ◽  
Tieh-Yong Koh
Keyword(s):  
Water Vapor ◽  
Standard Deviation ◽  
The Other ◽  
Mean Square ◽  
Atmospheric Infrared Sounder ◽  
Limb Effect ◽  
Atmospheric Window ◽  
The Mean ◽  
Optimal Set ◽  
Atmospheric Windows

Abstract A statistical method to correct for the limb effect in off-nadir Atmospheric Infrared Sounder (AIRS) channel radiances is described, using the channel radiance itself and principal components (PCs) of the other channel radiances to account for the multicollinearity. A method of selecting an optimal set of predictors is proposed and demonstrated for one- and two-PC predictors. Validation results with a subset of AIRS channels in the spectral region 649–2664 cm−1 show that the mean nadir-corrected brightness temperature (BT) is largely independent of scan angle. More than 66% of the channels have a root-mean-square (rms) bias less than 0.10 K after nadir correction. Limb effect on the standard deviation (SD) of BT is discernible at larger scan angles, mainly for the atmospheric windows and the water vapor channels around 6.7 μm. After nadir correction, nearly all atmospheric window channels unaffected by solar glint and more than 76% of water vapor channels examined have BT SDs brought closer to nadir values. For the window channels affected by solar glint (wavenumber &gt; 2490 cm−1), BT SDs at the scan angles with the strongest impact from solar reflection were improved on average by more than 0.6 K after nadir correction.

scholarly journals Personality and Motivation: A Correlation study among Sports Person

2019 ◽  
Vol 6 (4) ◽  
pp. 5-13
Author(s):  
M Keerthika ◽  
S Punithavathi
Keyword(s):  
Standard Deviation ◽  
Gender Difference ◽  
Correlation Coefficient ◽  
Significant Relationship ◽  
Correlation Study ◽  
Motivation Factors ◽  
The Mean ◽  
The Individual ◽  
Age Range ◽  
The Relationship

In this competitive world, it is essential to grab the sportive nature of sports persons. For different personality type of the individual the motive to engage in sports also varies from person to person. The aim of the present study is to determine the relationship between personality and motivation among sports persons and to identify the gender difference of personality and motivation factors. The sample of this study was 120 sports persons out of which 60 were males and 60 were females belonging to the age range of 18 -30 years. The mean, standard deviation and Pearson’s correlation coefficient were used for analysing the data. Results indicate that there is no significant relationship between Personality and Motivation type of sports persons.

scholarly journals Prevalencia de síndrome de burnout en los estudiantes de la Carrera de Enfermería de la Universidad Central del Ecuador

2020 ◽  
Vol 4 (8) ◽  
pp. 38-54
Author(s):  
Luzmila De Jesús Carvajal Andrade ◽  
◽  
Belén del Rocío Logacho Villacís ◽  
Ramiro Rogelio Rojas Jaramillo ◽  
◽  
...  
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Key Words ◽  
Nursing School ◽  
The Other ◽  
Burnout Syndrome ◽  
Information Analysis ◽  
Academic Burnout ◽  
Upper Limit ◽  
The Mean

This research has been conducted in order to determine the Prevalence of the burnout syndrome among students from third to eighth semester who are attending the Nursing School. It was a prevalence study; the data were collected using the survey’s technique, in a questionnaire divided in five sections applied to 172 students. The information analysis was calculated using the Mean method and the Standard Deviation for the Academic burnout, while for the Labor burnout it was utilized the punctuation of: high, medium and low scales. The outcome results showed that the prevalence of the burnout Syndrome in both academic and labor was low. The 2.3 % of students had the Academic burnout, (Confidence interval: 95%, lower limit: 0.44% and upper limit: 4.21%) with a probability of 3.52%, on the other hand the Labor burnout was of 4% among students in the shifting internship, with a probability of 1.22%. Key words: Syndrome burnout, Stress, nursing.

scholarly journals Measuring the Density Fluctuation From the Cluster Gas Mass Function

1999 ◽  
Vol 183 ◽  
pp. 267-267
Author(s):  
K. Shimasaku
Keyword(s):  
Density Fluctuation ◽  
Mass Function ◽  
Baryon Density ◽  
Density Parameter ◽  
Clusters Of Galaxies ◽  
Fluctuation Spectrum ◽  
The Mean ◽  
Image Position ◽  
The Universe

We derive the gas mass function of clusters of galaxies to measure the density fluctuation spectrum on cluster scales. The baryon abundance confined in rich clusters is computed from the gas mass function and compared with the mean baryon density in the universe which is predicted by the BBN. This baryon fraction and the slope of the gas mass function put constraints on σ8 and the slope of the fluctuation spectrum. Adopting the density parameter of baryons Ωbh2 = 0.0175 ± 0.0075 and assuming that , we find for h = 0.7 ± 0.1. Our value of σ8 is independent of Ω0 and thus we can estimate Ω0 by combining σ8 as obtained in this study with those from Ω0-dependent analyses to date. Constraints are also derived for CDM and CHDM models.

A Comparison of Techniques for Particle Rebound Measurement in Gas Turbine Applications

2015 ◽  
Author(s):  
Jeffrey P. Bons ◽  
Rory Blunt ◽  
Steven Whitaker
Keyword(s):  
Standard Deviation ◽  
Velocity Distribution ◽  
Gas Turbine ◽  
Correlation Coefficient ◽  
Strong Dependence ◽  
Individual Particle ◽  
Aluminum Surface ◽  
Trajectory Data ◽  
Mean Velocity ◽  
The Mean

The rebound characteristics of 100–500μm quartz particles from an aluminum surface were imaged using the particle shadow velocimetry (PSV) technique. Particle trajectory data were acquired over a range of impact velocity (30–90 m/s) and impact angle (20°–90°) typical for gas turbine applications. The data were then analyzed to obtain coefficients of restitution (CoR) using four different techniques: (1) individual particle rebound velocity divided by the same particle’s inbound velocity (2) individual particle rebound velocity divided by inbound velocity taken from the mean of the inbound distribution of velocities from all particles (3) rebound velocity distribution divided by inbound velocity distribution related using distribution statistics and (4) the same process as (3) with additional precision provided by the correlation coefficient between the two distributions. It was found that the mean and standard deviation of the CoR prediction showed strong dependence on the standard deviation of the inbound velocity distribution. The two methods that employed statistical algorithms to account for the distribution shape [methods (3) and (4)] actually overpredicted mean CoR by up to 6% and CoR standard deviation by up to 100% relative to method (1). The error between the methods is shown to be a strong (and linear) function of correlation coefficient, which is typically 0.2–0.6 for experimental CoR data. Non-Gaussianity of the distributions only accounts for up to 1% of the error in mean CoR, and this largely from the non-zero skewness of the inbound velocity distribution. Particle rebound data acquired using field average techniques that do not provide an estimate of correlation coefficient are most accurately evaluated using method (2). Method (3) can be used with confidence if the standard deviation of the inbound velocity distribution is less than 10% of the mean velocity, or if a linear correction based on an assumed correlation coefficient is applied.

The Link between Multiplicative Scatter Correction (MSC) and Standard Normal Variate (SNV) Transformations of NIR Spectra

1994 ◽  
Vol 2 (1) ◽  
pp. 43-47 ◽  
Author(s):  
M.S. Dhanoa ◽  
S.J. Lister ◽  
R. Sanderson ◽  
R.J. Barnes
Keyword(s):  
Particle Size ◽  
Standard Deviation ◽  
Correlation Coefficient ◽  
Size Effects ◽  
Scatter Correction ◽  
Standard Normal Variate ◽  
Multiplicative Scatter Correction ◽  
Standard Normal ◽  
Alternative Approaches ◽  
The Mean

We demonstrate that set-dependent multiplicative scatter correction and set-independent standard normal variate transformations of NIR spectra are linearly related as theoretically expected. It is shown that the mean and standard deviation of the set-mean-spectrum together with the correlation coefficient between each individual spectrum and set-mean-spectrum are required to link these two transformations. It is through these three quantities, that set-dependency is incorporated into spectra derived by application of multiplicative scatter correction. MSC and SNV are two alternative approaches to reduce particle size effects and they are interconvertible.

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