scholarly journals PRELIMINARY STATISTICAL ANALYSIS OF THE PROJECTION OF THE VELOCITY OF THE HYDROGEN MOLECULE USING A NOMOGRAM

2020 ◽  
pp. 103-110
Keyword(s):  
Statistical Analysis ◽  
Normal Distribution ◽  
Hydrogen Molecule ◽  
Initial Statistical Analysis

This article provides an initial statistical analysis of the projection of the velocity of the hydrogen molecule. Checked for normal distribution according to signs of conformity. In it, Kolmagorov's sign, 𝒳2 (xi - squared) sign, 𝜔 2 - sign and other signs were checked for normalcy. We examined the normality of the general set related to the projection of the velocity of the hydrogen molecule in 7 different ways, and in all cases concluded that the 𝐻𝑜 hypothesis was correct.

scholarly journals Online Tests in the Trend of Education 4.0: An Empirical Study in Mathematics at High Schools of Can Tho City

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Tuan Anh Bui ◽  
Nghia Huu Nguyen ◽  
Thao Thi Thu Tran ◽  
Anh Ngoc Phuong Nguyen
Keyword(s):  
High Schools ◽  
Statistical Analysis ◽  
Empirical Study ◽  
Natural Disasters ◽  
Assessment Of Learning ◽  
Can Tho City ◽  
Evaluation Of Learning ◽  
Online Tests ◽  
Experimental Group ◽  
Initial Statistical Analysis

In the trend of Education 4.0, the assessment of learning results through online tests is increasingly widespread and important because of its usability and mobility. In addition, it is also adaptable in the volatile situations of today's society such as natural disasters, epidemics, war, etc. The paper presents the results of an empirical study in Mathematics at high schools in Can Tho city on the comparison of outcomes between online tests and paper tests. The initial statistical analysis results show that the evaluation of learning results by online tests has high consensus among the experimental group. Furthermore, the advantages and suggestions for improvement are also pointed out and discussed in this work.

scholarly journals Verification of normal distribution of welding distortions

2019 ◽  
Vol 91 (3) ◽  
Author(s):  
Damian Grzesiak ◽  
Jarosław Plichta
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Normal Distribution ◽  
Sheet Metal ◽  
Welding Process ◽  
Experiment Planning ◽  
Geometrical Parameters ◽  
Butt Welds ◽  
Planning Methods ◽  
Smirnov Test

The aim of this paper is to answer the question of the distribution of welding distortions. The MIG method was used to make 31 butt welds of 0H18N9 sheet metal, of 6 mm thickness and dimensions 150x350 mm. All joints are made with constant parameters of the welding process. Statistical analysis of the distribution and Kolomogorov-Smirnov test were used in this paper. On the grounds of the analysis it was proved that the distribution of welding deformations is a normal distribution. This justifies the use of experiment planning methods and the use of average values. The relatively high value of the standard deviation makes it necessary to take into account the geometrical parameters of the joint.

scholarly journals Volatility of Jakarta Islamic Index

2014 ◽  
Vol 6 (2) ◽  
pp. 207-222
Author(s):  
Hendri Tanjung
Keyword(s):  
Statistical Analysis ◽  
Normal Distribution ◽  
Stock Exchange ◽  
Daily Data ◽  
Using Data ◽  
Simple Statistical Analysis

Volatility of Jakarta Islamic Index. This study investigates the volatility of Jakarta Islamic Index (JII) in Jakarta Stock Exchange. The method that used in this research is used a simple statistical analysis. The normality of JII return is analyzed to answer whether the return of JII follows normal distribution. By using data of Jakarta Islamic Index from 2nd March 2009 to 30th October 2013 (1122 daily data), it is found that the distribution of return of JII is not normal, even the 5 sigma occurred. This means the return of Jakarta Islamic Index is much volatile than the theory predicted. This will make too much gain or loss in one day in the economy  DOI:10.15408/aiq.v6i2.1231

scholarly journals Mendel’s pea crosses: varieties, traits and statistics

Hereditas ◽  
2019 ◽  
Vol 156 (1) ◽  
Author(s):  
T. H. Noel Ellis ◽  
Julie M. I. Hofer ◽  
Martin T. Swain ◽  
Peter J. van Dijk
Keyword(s):  
Statistical Analysis ◽  
Normal Distribution ◽  
Standard Normal Distribution ◽  
Data Sets ◽  
Crossing Experiments ◽  
Independent Variables ◽  
F2 Population ◽  
A Value ◽  
Segregation Ratios ◽  
Standard Normal

Abstract A controversy arose over Mendel’s pea crossing experiments after the statistician R.A. Fisher proposed how these may have been performed and criticised Mendel’s interpretation of his data. Here we re-examine Mendel’s experiments and investigate Fisher’s statistical criticisms of bias. We describe pea varieties available in Mendel’s time and show that these could readily provide all the material Mendel needed for his experiments; the characters he chose to follow were clearly described in catalogues at the time. The combination of character states available in these varieties, together with Eichling’s report of crosses Mendel performed, suggest that two of his F3 progeny test experiments may have involved the same F2 population, and therefore that these data should not be treated as independent variables in statistical analysis of Mendel’s data. A comprehensive re-examination of Mendel’s segregation ratios does not support previous suggestions that they differ remarkably from expectation. The χ2 values for his segregation ratios sum to a value close to the expectation and there is no deficiency of extreme segregation ratios. Overall the χ values for Mendel’s segregation ratios deviate slightly from the standard normal distribution; this is probably because of the variance associated with phenotypic rather than genotypic ratios and because Mendel excluded some data sets with small numbers of progeny, where he noted the ratios “deviate not insignificantly” from expectation.

Statistical Analysis of the Roundness Error Data

2012 ◽  
Vol 472-475 ◽  
pp. 869-874 ◽  
Author(s):  
Zhao Peng Dong ◽  
Li Ling Huang ◽  
Hai Ting Xie ◽  
Fu Gui Huang
Keyword(s):  
Mathematical Model ◽  
Computer Simulation ◽  
Statistical Analysis ◽  
Normal Distribution ◽  
Mathematical Knowledge ◽  
Measurement Data ◽  
Roundness Error ◽  
Main Emphasis ◽  
The Mathematical Model ◽  
Roundness Measurement

In order to simulate the actual roundness measurement accurately, must find the mathematical model of the actual roundness data, the paper’s main emphasis is doing statistical analysis by plenty of measurement data of roundness, using mathematical knowledge to prove that the actual characteristics of roundness parameters obey the normal distribution, and providing the basis for subsequent computer simulation in the future

X-Ray Diffraction Analysis Analyze the Error of Residual Stress by Using Mathematical Statistics

2010 ◽  
Vol 43 ◽  
pp. 687-690
Author(s):  
Ai Xin Feng ◽  
Chuan Chao Xu ◽  
Yu Peng Cao ◽  
Huai Yang Sun ◽  
Gui Fen Ni ◽  
...  
Keyword(s):  
Residual Stress ◽  
Aluminum Alloy ◽  
Statistical Analysis ◽  
Diffraction Analysis ◽  
Hypothesis Testing ◽  
Normal Distribution ◽  
X Ray Diffraction ◽  
X Ray ◽  
7050 Aluminum Alloy ◽  
Stress Error

X-ray diffraction analysis methods analyze the residual stress the same location for 50 times of 7050 aluminum alloy. And taking residual stress error for statistical analysis, through hypothesis testing and analysis of the residual stress error Square diagram, obtain X-ray diffraction the residual stress error of the 7050 aluminum alloy approximately obey normal distribution.

scholarly journals Statistical Analysis of Basketball Teams Through Normal Distribution and R Programming

2020 ◽  
Vol 4 (9) ◽  
Author(s):  
Megan Wang
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Probability Density Function ◽  
Normal Distribution ◽  
Sports Analytics ◽  
R Programming Language ◽  
General Improvement ◽  
The Mean ◽  
R Programming ◽  
Two Parameters

Basketball has existed for almost 130 years, becoming one of the most famous sports worldwide by affecting millions of lives and having national and global tournaments. With the general improvement of people's concern and love for sports competition, sports analytics’ role will become more prominent. Hence, this paper combines the relevant knowledge of statistics and typical basketball competition cases from NBA, expounding the application of statistics in sports competition. The paper first examines the importance of normal distribution (also called Gaussian distribution) in statistics through its probability density function and the function's graph. The function has two parameters: the mean for the maximum and standard deviation for the distance away from the mean[1]. By compiling datasets of past teams and individuals for their basketball performances and making simple calculations of their standard deviation and mean, the paper constructs normal distribution graphs using the R programming language. Finally, the paper examines the Real Plus-Minus value and its importance in basketball.

scholarly journals Statistical control of the production process of rolled products

2018 ◽  
Vol 20 (20) ◽  
pp. 26-31 ◽  
Author(s):  
Krzysztof Knop
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Normal Distribution ◽  
Control Charts ◽  
Statistical Control ◽  
Measurement Results ◽  
Corrective Actions ◽  
Fmea Method ◽  
The Stability ◽  
Level Of Risk

Abstract The article presents the results of the use of SPC tools, i.e. control charts and indicators of the qualitative capability to assess the stability and capability of the production process of rolled products - I-sections. Statistical analysis of the collected data regarding the selected feature of the analysed product - the width of the foot, and the normality of the distribution were done, which showed that the obtained distribution of measurement results is not a normal distribution. As a result, appropriate SPC procedures for non-normal distribution were used. The Pareto-Lorenzo diagram and FMEA method were also used to obtain information about the structure of non-conformities of the analysed product and the level of risk associated with them. This information was used to propose corrective actions and improve the production process of rolled products.

scholarly journals Nonparametric Methods in the Analysis of the Quality of Kernel of Selected Winter Wheat Cultivars

2021 ◽  
Vol 25 (1) ◽  
pp. 125-134
Author(s):  
Magdalena Ćwiklinska ◽  
Zofia Hanusz ◽  
Jakub Soja ◽  
Renata Polak
Keyword(s):  
Statistical Analysis ◽  
Winter Wheat ◽  
Normal Distribution ◽  
Analysis Of Variance ◽  
Nonparametric Methods ◽  
Experimental Results ◽  
Average Weight ◽  
Wheat Cultivars ◽  
Winter Wheat Cultivars

Abstract The paper presents a statistical analysis of weight and diameter of kernel obtained for eight investigated winter wheat cultivars. Preliminary analyses of experimental results, such as compliance with a normal distribution, equality of variance for particular cultivars, and occurrence of outliers proved that there is no justification for the use of a traditional one-way analysis of variance for verification of hypotheses according to which weight and diameter of grains of the investigated winter wheat cultivars do not differ. A nonparametric Kruskal-Wallis test was used for verification of hypotheses which based on the experimental results enabled to reject both hypotheses. Further, simultaneous average weight and diameters of grain of the investigated cultivars were compared with the use of Nemenyi-Dunn test. The applied test enabled to conclude which cultivars had a significantly higher weight than the others. Analogous comparisons were carried out for the diameter of kernels of the investigated winter wheat cultivars.

Sign in / Sign up

Export Citation Format

Share Document