The statistical analysis of non-normal (real?) data

1979 ◽  
Vol 4 (10) ◽  
pp. 236-239 ◽  
Author(s):  
I.A. Nimmo ◽  
G.L. Atkins
Keyword(s):  
Statistical Analysis ◽  
Real Data

scholarly journals Efficiency of sector sampling for estimating juniper forest attributes vs. fixed area plot

2017 ◽  
Vol 63 (No. 10) ◽  
pp. 463-469
Author(s):  
Seraj Mohammad Hussein ◽  
Kiani Bahman
Keyword(s):  
Statistical Analysis ◽  
Sampling Error ◽  
Real Data ◽  
Cost Effective ◽  
Mountain Areas ◽  
Crown Cover ◽  
Significant Difference ◽  
Fixed Area ◽  
Sector Angle ◽  
Juniper Forests

Juniper forests grow in mountain areas and many difficulties are encountered in their sampling. Sector sampling as an unbiased and cost-effective method was tested for the sampling of a 12.5-ha juniper forest. To begin with, a point-map of trees was created and 50 quadrats were determined systematically. Fixed area plots were measured within these 50 × 50 m quadrats. In each quadrat, eight sectors with 45° angle were determined. One-sector and two-sector scenarios randomly besides four-sector scenario systematically were conducted. Accuracy and precision of sampling methods were compared. Also, statistical analysis was conducted to compare sector sampling scenarios with fixed area plot (FAP) and real data. Results showed that four-sector scenario estimates were close to FAP method in precision and accuracy. Statistical analysis showed that there was no significant difference between sector sampling scenarios and FAP and in real data. But in correlation analysis only the four-sector scenario could compete with FAP method. Regarding consumed time and sampling error simultaneously, the efficiency of sector sampling was higher than that of FAP method for estimating density and close to FAP method for estimating crown cover. It can be concluded that in laborious situations such as in juniper forests, sector sampling can be competitive with FAP method with noticeable parsimony. But more study is still needed to decrease sampling error and optimize sector angle with the purpose of cost saving.

The `seed-skewness' integration method generalized for three-dimensional Bragg peaks

2003 ◽  
Vol 36 (6) ◽  
pp. 1475-1479 ◽  
Author(s):  
J. Peters
Keyword(s):  
Statistical Analysis ◽  
High Resolution ◽  
Integration Method ◽  
A Priori ◽  
Reciprocal Lattice ◽  
Three Dimensional ◽  
Real Data ◽  
Area Detector ◽  
Peak Integration ◽  
Electronic Detector

The integration of the three-dimensional profile of each node of the reciprocal lattice without ana priorimodelling of the shape of the reflections is a prerequisite in order to improve the capability of area detectors in diffraction studies. Bolotovskyet al.[J. Appl. Cryst.(1995),28, 86–95] published a new method of area-detector peak integration based on a statistical analysis of pixel intensities and suggested its generalization for processing of high-resolution three-dimensional electronic detector data. This has been done in the present work, respecting the special requirements of data collected from neutron diffraction. The results are compared with other integration methods. It is shown that the seed-skewness method is successful in giving very reliable results and simultaneously optimizes the standard deviations. The integration procedures are applied to real data, which are refined and compared with benchmark results.

scholarly journals Statistical analysis of the community lockdown for COVID-19 pandemic

2021 ◽  
Author(s):  
Shaocong Wu ◽  
Xiaolong Wang ◽  
Jingyong Su
Keyword(s):  
Statistical Analysis ◽  
Simulation Models ◽  
Real Data ◽  
Control Measures ◽  
Complex Dynamic ◽  
Spreading Process ◽  
Modeling And Analysis ◽  
Basic Assumptions ◽  
Global Pandemic ◽  
Multiple Variables

AbstractAs the global pandemic of the COVID-19 continues, the statistical modeling and analysis of the spreading process of COVID-19 have attracted widespread attention. Various propagation simulation models have been proposed to predict the spread of the epidemic and the effectiveness of related control measures. These models play an indispensable role in understanding the complex dynamic situation of the epidemic. Most existing work studies the spread of epidemic at two levels including population and agent. However, there is no comprehensive statistical analysis of community lockdown measures and corresponding control effects. This paper performs a statistical analysis of the effectiveness of community lockdown based on the Agent-Level Pandemic Simulation (ALPS) model. We propose a statistical model to analyze multiple variables affecting the COVID-19 pandemic, which include the timings of implementing and lifting lockdown, the crowd mobility, and other factors. Specifically, a motion model followed by ALPS and related basic assumptions is discussed first. Then the model has been evaluated using the real data of COVID-19. The simulation study and comparison with real data have validated the effectiveness of our model.

scholarly journals Statistical Analysis for Prognosis of a Photochemical Smog Episode

2013 ◽  
Vol 9 (2) ◽  
pp. 20-24
Author(s):  
Camelia Gavrilă ◽  
Florinela Ardelean ◽  
Adriana Coman ◽  
Elena Burchiu
Keyword(s):  
Statistical Analysis ◽  
Solar Radiation ◽  
Prognostic Value ◽  
Meteorological Parameters ◽  
Real Data ◽  
Global Solar Radiation ◽  
Photochemical Smog ◽  
Climatic Parameters ◽  
Essential Information ◽  
Pollutant Concentrations

Abstract In this paper we describe the evaluation of various climatic parameters in establishing their prognostic value in a photochemical smog episode. Our application was validated using real data from the “Cercul Militar National” and “Sos. Mihai Bravu nr. 47-49”, from April 2008 to May 2008. The study was performed on hour averages of pollutant concentrations and meteorological parameters and the statistical analysis was based on multiple regressions. We concluded by using mathematical and statistical methods, [1], that an accurate Global Solar Radiation is one of the most important and essential information in the pollution report.

An Example of A Method of Statistical Analysis of a Grazing Experiment

1972 ◽  
Vol 79 (1) ◽  
pp. 165-167 ◽  
Author(s):  
D. Conniffe ◽  
D. Browne ◽  
M. J. Walshe
Keyword(s):  
Statistical Analysis ◽  
Experimental Design ◽  
Real Data ◽  
Grazing Experiment ◽  
Statistical Validity

SUMMARYConniffe, Browne & Walshe (1970) proposed a form of experimental design and statistical analysis for grazing experiments. The original paper did not include any example of the analysis on real data. This note presents such an example and makes some comments on the statistical validity of the method of analysis.

scholarly journals A teaching tool about the fickle p value and other statistical principles based on real-life data

2021 ◽  
Author(s):  
Salem Alawbathani ◽  
Mehreen Batool ◽  
Jan Fleckhaus ◽  
Sarkawt Hamad ◽  
Floyd Hassenrück ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Real Life ◽  
Real Data ◽  
P Value ◽  
Life Data ◽  
Real Life Data ◽  
Random Samples ◽  
Poor Understanding ◽  
The Impact

AbstractA poor understanding of statistical analysis has been proposed as a key reason for lack of replicability of many studies in experimental biomedicine. While several authors have demonstrated the fickleness of calculated p values based on simulations, we have experienced that such simulations are difficult to understand for many biomedical scientists and often do not lead to a sound understanding of the role of variability between random samples in statistical analysis. Therefore, we as trainees and trainers in a course of statistics for biomedical scientists have used real data from a large published study to develop a tool that allows scientists to directly experience the fickleness of p values. A tool based on a commonly used software package was developed that allows using random samples from real data. The tool is described and together with the underlying database is made available. The tool has been tested successfully in multiple other groups of biomedical scientists. It can also let trainees experience the impact of randomness, sample sizes and choice of specific statistical test on measured p values. We propose that live exercises based on real data will be more impactful in the training of biomedical scientists on statistical concepts.

The Data on Gender Inequality in Philosophy: The Spanish Case

Hypatia ◽  
2020 ◽  
Vol 35 (4) ◽  
pp. 646-666
Author(s):  
Obdulia Torres González
Keyword(s):  
Statistical Analysis ◽  
Gender Inequality ◽  
Cognitive Abilities ◽  
International Comparisons ◽  
Real Data ◽  
Gender Imbalance ◽  
Introductory Courses ◽  
Research Personnel ◽  
National System ◽  
International Scope

AbstractThis article examines gender imbalance in philosophy using statistical analysis of philosophy professionals and students in Spain. It is the only study on an international scope that provides complete, real data of an entire national system. This analysis shows that among teaching and research personnel, women make up 25% of the total, among full professors they represent 12%, and the glass-ceiling index in the field is the same as that in engineering. For the study, I resorted to a normalization of indicators to allow for international comparisons, which I have done using the reports and analyses available in other countries. In the second part of the article, I use the Spanish data to test some recent hypotheses on gender imbalance in philosophy. The data does not confirm the theory of Neven Sesardic and Rafael de Clercq, which attributes the imbalance to differences in cognitive abilities (Sesardic and Clercq 2014). However, the data does partially confirm the study by Molly Paxton, Carrie Figdor, and Valerie Tiberius regarding the dissuasive effect of introductory courses in philosophy (Paxton, Figdor, and Tiberius 2012), as well as that by Sarah Leslie and her colleagues on the field-specific abilities belief hypothesis (Leslie et al. 2015).

scholarly journals Statistical Analysis for Effect Factor to Pupils’ Level in Mathematical Course for Preparatory Education

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Hadeel Ismail Mustafa ◽  
Mohamed Abdulrahman Abdulhamed ◽  
Zainab Ibrahim Othman
Keyword(s):  
Statistical Analysis ◽  
Educational Institution ◽  
Real Data ◽  
Effect Factors ◽  
Preparatory School ◽  
Effect Factor ◽  
Student Failure ◽  
Educational Foundation ◽  
Low Levels ◽  
Ability Student

In an educational foundation whose objective is to contribute to the enhancement of the finest education, the improvement of quality in an educational institution is verified by providing the best services which are better meeting each student’s need. General, in preparatory school in Iraq—especially in Basra—the students’ ability in mathematical courses is low levels based General, in preparatory school in Iraq—especially in Basra—the students’ ability in mathematical courses is low levels based. In this study, we discussed the effect of diverse factors on student failure and success using real data collected in many of the schools in Basra. These data were analyzed using SPSS version 0.23. At the end of the study, we identified the factors that could have affected the students’ capabilities (e.g., teachers’ ability, student effect factors, and institutional ability).

scholarly journals Frequency-smoothing encryption: preventing snapshot attacks on deterministically encrypted data

2018 ◽  
pp. 277-313 ◽  
Author(s):  
Marie-Sarah Lacharité ◽  
Kenneth G. Paterson
Keyword(s):  
Statistical Analysis ◽  
Frequency Analysis ◽  
Real Data ◽  
Searchable Encryption ◽  
Encrypted Data ◽  
Attack Model ◽  
Deterministic Encryption ◽  
Classical Technique ◽  
Inference Attacks ◽  
Provably Secure

Statistical analysis of ciphertexts has been recently used to carry out devastating inference attacks on deterministic encryption (Naveed, Kamara, and Wright, CCS 2015), order-preserving/revealing encryption (Grubbs et al., S&P 2017), and searchable encryption (Pouliot and Wright, CCS 2016). At the heart of these inference attacks is classical frequency analysis. In this paper, we propose and evaluate another classical technique, homophonic encoding, as a means to combat these attacks. We introduce and develop the concept of frequency-smoothing encryption (FSE) which provably prevents inference attacks in the snapshot attack model, wherein the adversary obtains a static snapshot of the encrypted data, while preserving the ability to efficiently and privately make point queries. We provide provably secure constructions for FSE schemes, and we empirically assess their security for concrete parameters by evaluating them against real data. We show that frequency analysis attacks (and optimal generalisations of them for the FSE setting) no longer succeed.

scholarly journals Efficiency assessment of e-learning compared to traditional education using Principal Component Analysis and verification of Genetic Algorithms: تقييم كفاءة التعليم الإلكتروني مقارنة بالتعليم التقليدي باستخدام تحليل المكونات الأساسية والتحقق بالخوارزميات الجينية

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Firas Shawkat Hamid
Keyword(s):  
Principal Component Analysis ◽  
Genetic Algorithms ◽  
Factor Analysis ◽  
Statistical Analysis ◽  
Technological Development ◽  
Multivariate Data ◽  
Principal Component ◽  
Real Data ◽  
Component Analysis ◽  
E Learning

Multivariate data analysis is one of the common techniques that are used in the analysis of the main compounds that perform the process of converting a large number of related variables into a smaller number of unrelated compounds, In the case of the emergence of anomalous values, which can be detected in many ways, the adoption of the matrix of contrast and common contrast will lead to misleading results in the analysis of the principal compounds. Therefore, many of the phenomena that consist of a large group of variables that are difficult to deal with initially, and the process of interpreting these variables becomes a complex process, so reducing these variables to a lower setting is easier to deal with, and it is the aspiration of every researcher working in the field of main compounds analysis or factor analysis. Because of technological development and the ability to communicate by audio and video interaction at the same time, on this research, a multivariate data collection process was conducted, where an evaluation of the efficiency of e-learning was studied and analyzed by highlighting the process of analyzing real data using factor analysis by the Principal Component Analysis method. This is one of the techniques used to summarize and shorten the data and through the use of the SPSS: Statistical Packages for Social Sciences Program, Thus, it will be noted that the subject of the paper will flow into the concept of Data mining also, And then achieve it using genetic algorithms using the simulation program with its final version, which is MATLAB, also using the method of Multiple Linear Regression Procedure to find the arrangement of independent variables by calculating the weight of the independent variable. Total results were obtained for the eigenvalues of the stored correlation matrix or the rotating factor matrix, The study required conducting statistical analysis in the mentioned way and by reducing the number of variables without losing much information about the original variables and its aim is to simplify its understanding and reveal its structure and interpretation, The study required conducting statistical analysis in the mentioned way and by reducing the number of variables without losing much information about the original variables and its aim is to simplify its understanding and reveal its structure and interpretation. In addition to reaching a set of conclusions that were discussed in detail also the addition to the important recommendations.

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