scholarly journals STATISTICAL ANALYSIS OF BOREHOLE SAMPLE DATA FROM THE LIWU COPPER MINE, SICHUAN, SOUTHWESTERN CHINA

1996 ◽  
Vol 7 (1-2) ◽  
pp. 29-35
Author(s):  
Zhaoping Yang ◽  
Zijin Li ◽  
Shuangquan Zhang
Keyword(s):  
Statistical Analysis ◽  
Southwestern China ◽  
Copper Mine ◽  
Sample Data

Ukuran Gejala Pusat Data Belum Dikelompokan(Kebakaran di Provinsi-Provinsi Tertentu di Indonesia Tahun 2015-2016)

2020 ◽  
Author(s):  
Riska Nurhapsari Santoso ◽  
Yudis Satrio Utomo ◽  
Yuliani Luturmasse
Keyword(s):  
Statistical Analysis ◽  
Frequency Distribution ◽  
Data Center ◽  
Grouped Data ◽  
Sample Data ◽  
Calculated Average

Abstract - Statistics is a framework of theories and methods that have been developed to collect, analyze, and write sample data in order to obtain useful conclusions. Statistics is the science of ways of collecting, classifying, analyzing, and searching for information related to the collection of data that investigations and conclusions based on evidence in the form of figures.Based on the results of the study can be concluded as follows: the size of the symptoms of the data center has not been grouped is the data compiled into the frequency distribution so that it does not have class intervals and midpoints of the class. Symptom Size Un-Grouped Data Center The size of the data center included in the statistical analysis is the calculated average (mean), median, mode, and fractil (quartile, decile, percentile)

scholarly journals Current State and Development Prospects of the Russian Factoring Market (Brief Statistical Analysis)

2021 ◽  
Vol 18 (4) ◽  
pp. 22-34
Author(s):  
Lyubov Yu. Arkhangelskaya ◽  
Viktor N. Salin
Keyword(s):  
Statistical Analysis ◽  
Financial Intermediation ◽  
Professional Community ◽  
The State ◽  
Third Party ◽  
Annual Growth Rate ◽  
Market Segment ◽  
Accounts Payable ◽  
Sample Data ◽  
Business Structures

Factoring is a fairly new way for Russia to finance the accounts payable and receivable of business structures by specialized companies or credit institutions and their divisions (Factors) against the assignment of claims against one of the parties (buyer or seller) of a sale and purchase transaction of products or property to a third party (Factor) is currently developing at a high pace. On average, according to sample data for 2011 -2019 the annual growth rate of the volumes of financing of accounts payable and receivable of companies in Russia due to factoring operations increased by 20%, which in absolute terms amounted to 303.3 billion rubles, and reached by 2019 - 3.5 trillion rubles.However, there is still no established definition of this economic category in the Civil Code of the Russian Federation. In the scientific and educational foreign and domestic literature there are somewhat contradictory interpretations of the classifications of the types of factoring, there is no legislatively established system of statistical indicators characterizing this segment of the financial intermediation services market. The lack of a developed regulatory framework for regulating relations in this market segment slows down its development, necessitates improving both Russian legislation and methodological support for a comprehensive statistical analysis of the state and development of this market segment. In this regard, the purpose of this study is to develop a methodology for a comprehensive statistical analysis of the market segment of financial intermediation services, to determine the prevailing sectoral, territorial and types of proportions related to the scale of business of the parties to the factoring agreement in this market segment using the statistical methodology for analyzing the series of dynamics and attributive groupings of the main indicators characterizing the state and development of the Russian factoring market. Based on the theoretical analysis, the author’s interpretation of the content of the economic category “factoring” is given, a system of indicators is proposed that characterizes factoring as a type of financial intermediation services (object of research), based on the development of the Association of factoring companies, Rosstat, expert agencies (for example, “Expert RA”); the features of the formation of statistical groupings (series: attributive, variation, dynamics) for various purposes of analyzing the market of factoring services are revealed, the author’s method of complex statistical analysis of any segment of the financial intermediation services market, which is the subject of research, is presented. The results of approbation of the methodology for a comprehensive statistical analysis of the Russian factoring market based on sample data for 2011 – 2019 are presented, conclusions are drawn about the dynamics of the main indicators of the factoring market development, structural shifts and changes in proportions in this market segment, a forecast of expected changes in the Russian factoring market for  2021 is made, incl. and influenced by the Covid-19 pandemic.The results of this study are aimed at developing a methodology for a comprehensive statistical analysis of factoring as a segment of the financial intermediation services market, including for the purposes of international comparisons of indicators of the state and development of the Factors and their clients.They can be useful to the professional community of factoring companies (Factors), business structures - consumers of factoring services, and also be used in educational activities in the preparation of financial specialists in economic universities of the country.

NUANCES OF IDENTIFICATION FOR NORMAL DISTRIBUTION

2020 ◽  
Vol 11 (3) ◽  
pp. 176-183
Author(s):  
Vyacheslav M. Duplyakin
Keyword(s):  
Statistical Analysis ◽  
Normal Distribution ◽  
Numerical Procedure ◽  
Critical Conditions ◽  
Pearson Criterion ◽  
Statistical Series ◽  
Sample Data ◽  
Low Probability ◽  
Normal Law ◽  
The Given

Statistical analysis of sample data is an effective tool for researching trends in economic processes and their critical conditions. The techniques in statistical analysis that are widely used in practice are based on the assumption that the sample data being considered follows a normal distribution. In the article the author reveals that the application of the popular K. Pearson criterion of agreement in such problems to confirm normality distributions of sample data can lead to false conclusions, in cases where the original general population is distributed according to the normal law, and the criterion indicates a low probability of implementing the normality hypothesis. The author proposes a numerical procedure for studying the nuances of identifying the normality in sample data; it uses a novel technique that is based on reference statistical series which correspond to samples of a certain size with the given, fixed estimates of the expected value and standard deviation. The author presents a numerical modeling method and the results of studying the characteristics of sample data that affect the errors in the identification of the normality of the sampled populations. The performed numerical experiments allowed us to obtain statistical data for investigating the reliability of the identification of the sampled distributions. The author presented recommendations that can help to avoid errors in identifying normality.

scholarly journals Comparisons of Brightness Temperatures of Landsat-7/ETM+ and Terra/MODIS around Hotien Oasis in the Taklimakan Desert

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Yoshinari Oguro ◽  
Seiji Ito ◽  
Kiyoshi Tsuchiya
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Brightness Temperature ◽  
Observation Time ◽  
Taklimakan Desert ◽  
Desert Area ◽  
Brightness Temperatures ◽  
Sample Data ◽  
Landsat 7 ◽  
Terra Modis

The brightness temperature (BT) of Taklimakan Desert retrieved from the data of Landsat-7/ETM+ band 6 and Terra/MODIS band 31 and 32 indicates the following features: (1) good linear relationship between the BT of ETM+ and that of MODIS, (2) the observation time adjusted BT of ETM+ is almost equal to that of MODIS, (3) the BT of Terra/MODIS band 31 is slightly higher than that of band 32 over a reservoir while opposite feature is recognized over desert area, (4) the statistical analysis of 225 sample data of ETM+ in one pixel of MODIS for different landcovers indicates that the standard deviation and range of BT of ETM+ corresponding to one pixel of MODIS are0.45∘C,2.25∘Cfor a flat area of desert, while respective values of the oasis farmland and shading side of rocky hill amount to2.88∘C,14.04∘C, and2.80∘C,16.04∘C.

scholarly journals Hydrochemistry and Entropy-Based Groundwater Quality Assessment in the Suining Area, Southwestern China

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yunhui Zhang ◽  
Xiao Li ◽  
Ming Luo ◽  
Changli Wei ◽  
Xun Huang ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Groundwater Quality ◽  
Major Ions ◽  
Exchange Process ◽  
World Health ◽  
Southwestern China ◽  
Ion Exchange Process ◽  
Groundwater Samples ◽  
Entropy Weighted ◽  
Health Organization

Groundwater is an essential resource for sustainable development, whose quality is significant for human health. In the present study, twenty-eight groundwater samples were collected from domestic tube wells and public water supply wells in the Suining area, southwestern China. The integration of statistical analysis, correlations of ions, geomodelling, and entropy-weighted water quality index (EWQI) was carried out to clarify the hydrochemistry and groundwater quality in the study area. By the statistical analysis, the cations followed the concentration order as Ca2+> Na+> Mg2+> K+, while anions’ concentrations were HCO3− > SO42− > Cl− > NO3− > F−. Piper trilinear diagram showed the hydrochemical type was characterized as Ca-HCO3. Correlations of ions and geomodelling revealed the concentrations of major ions were mainly determined by carbonate dissolution and ion exchange process, and NO3− concentrations were controlled by agriculture activities. EWQI computation demonstrated that most of the groundwater samples possessed EWQI values higher than 100. Therefore, groundwater quality is lower than the permissible limit of the World Health Organization (WHO), suitable for drinking purposes in the Suining area. Our study provides vital knowledge for groundwater management in the Suining and other similar areas.

scholarly journals Statistical analysis of the spatial distribution of impurities in the snow cover in the vicinity of copper mine in the Middle Ural of Russia

2018 ◽  
Author(s):  
Irina Subbotina ◽  
Alexander Buevich ◽  
Alexander Medvedev ◽  
Alexander Sergeev ◽  
Marina Sergeeva ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Statistical Analysis ◽  
Snow Cover ◽  
Copper Mine

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

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