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)

Ukuran Gejala Data Belum Dikelompokan (Studi Kasus : Jumlah Warga Yang Meninggal Akibat Terjangkit Virus Covid-19 di Kota Depok Per-oktober 2020)

2020 ◽  
Author(s):  
Adellina Sylvira Azis ◽  
M.Alfarisi Farabbi ◽  
Dian Kristianto Tatarang ◽  
Aziiz firmansyach
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Geometric Mean ◽  
Measurement Data ◽  
Microsoft Excel ◽  
Sample Data ◽  
Harmonic Average ◽  
Symptom Measurement ◽  
The Right ◽  
Calculated Average

The statistic is a method developed for analyzing, analyzing, and compiling sample data to get the right data. Also, observation is needed to get accurate and concrete data. Various kinds of methods can be used to obtain the data, one of which is the Symptom Symptoms Data Center is the symptom data which is divided into two, namely the symptom center symptom data grouped and the data center symptom grouped. This journal will explain in detail the size of Symptoms in unclassified data centers Symptom Measurement of Unclassified Data Centers or also Symptom Size Single grouped data centers are data that are not arranged in a frequency distribution, so there are no category intervals and category midpoints. Symptom measurement data centers have not been grouped namely the calculated average (mean), measuring / geometric mean, harmonic average, tertiary average, median, mode, and fractile (quartile, decile, percentile). Measurement can use Microsoft Excel and SPSS applications

Exergy Analysis of Data Center Thermal Management Systems

2003 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Exergy Analysis ◽  
Thermal Control ◽  
Management Systems ◽  
World Systems ◽  
Sample Data ◽  
Potential Applications ◽  
Temperature Ranges

Data centers today contain more computing and networking equipment than ever before. As a result, a higher amount of cooling is required to maintain facilities within operable temperature ranges. Increasing amounts of resources are spent to achieve thermal control, and tremendous potential benefit lies in the optimization of the cooling process. This paper describes a study performed on data center thermal management systems using the thermodynamic concept of exergy. Specifically, an exergy analysis has been performed on sample data centers in an attempt to identify local and overall inefficiencies within thermal management systems. The development of a model using finite volume analysis has been described, and potential applications to real-world systems have been illustrated. Preliminary results suggest that such an exergy-based analysis can be a useful tool in the design and enhancement of thermal management systems.

scholarly journals Statistical Analysis of Word Frequency Distribution in Lithuanian Texts of Different Genres

2016 ◽  
Vol 55 (1) ◽  
pp. 61-69
Author(s):  
Neringa Bružaitė ◽  
Tomas Rekašius
Keyword(s):  
Statistical Analysis ◽  
Word Frequency ◽  
Frequency Distribution ◽  
Hierarchical Clustering ◽  
Distance Measure ◽  
Structural Type ◽  
Clustering Method ◽  
Jaccard Distance ◽  
Word Frequencies ◽  
Word Frequency Distribution

The paper examines Lithuanian texts of different authors and genres. The main points ofinterest – the number of words, the number of different words and word frequencies. Structural type distributionand Zipf’s law are applied for describing the frequency distribution of words in the text. It is obvious that thelexical diversity of any text can be defined by different words that are used in the text, also called vocabulary.It is shown that the information contained in a reduced vocabulary is enough for dividing the texts analyzedin this article into groups by genre and author using a hierarchical clustering method. In this case, distancesbetween clusters are measured using the Jaccard distance measure, and clusters are aggregated using the Wardmethod.

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.

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

scholarly journals On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

2009 ◽  
Vol 2009 ◽  
pp. 1-16 ◽  
Author(s):  
Jin Xia ◽  
Jie Mi ◽  
YanYan Zhou
Keyword(s):  
Maximum Likelihood ◽  
Lognormal Distribution ◽  
Existence And Uniqueness ◽  
Maximum Likelihood Estimators ◽  
Invariance Property ◽  
Type I ◽  
Grouped Data ◽  
Sample Data ◽  
Censored Sample ◽  
Two Parameters

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can be recorded instead. This is the so-called grouped data. In this paper, we will show the existence and uniqueness of the maximum likelihood estimators of the two parameters of the underlying lognormal distribution with Type-I censored data and grouped data. The proof was first established under the case of normal distribution and extended to the lognormal distribution through invariance property. The results are applied to estimate the median and mean of the lognormal population.

scholarly journals Species frequency distribution as a function of the surface area

2014 ◽  
Vol 53 (1) ◽  
pp. 87-98
Author(s):  
Anna J. Kwiatkowska
Keyword(s):  
Statistical Analysis ◽  
Surface Area ◽  
Frequency Distribution ◽  
Point Of View ◽  
Sample Plot ◽  
Statistical Point ◽  
Frequency Distributions ◽  
Species Frequency

Paper deals with the results of statistical analysis of the type of frequency distribution of species occuring in the field layers of two forest phytocoenoses. In the both cases frequency distributions were ranged out for the surface area of 1, 2, 4, 8, 16, 32 and 64 m<sup>2</sup>. The types of frequency distributions were determined on the grounds of the values of Fisher's and Pearson's K coefficients. Analysed distributions were classified into Pearson's system. Also the size of the sample plot at which the empirical frequency distributions were symetrical, from the statistical point of view, nad where they were U-shaped was determined.

Statistical Analysis of 100 Gbps per Wavelength SWDM VCSEL-MMF Data Center Links on a Large Set of OM3 and OM4 Fibers

2021 ◽  
pp. 1-1
Author(s):  
Pablo Torres-Ferrera ◽  
Giuseppe Rizzelli Martella ◽  
Antonino Nespola ◽  
Jose Castro ◽  
Bulent Kose ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Center ◽  
Large Set

INFANTILE SPASTIC HEMIPLEGIA IV. BIRTH WEIGHTS

PEDIATRICS ◽  
1955 ◽  
Vol 16 (4) ◽  
pp. 470-477
Author(s):  
Philip N. Hood ◽  
Meyer A. Perlstein
Keyword(s):  
Birth Weight ◽  
Statistical Analysis ◽  
Frequency Distribution ◽  
Sex Difference ◽  
Mental Defective ◽  
Premature Births ◽  
Total Group ◽  
Spastic Hemiplegia ◽  
The Mean ◽  
The Difference

This is a study of the birth weights of 190 patients with congenital spastic hemiplegia. Statistical analysis of these birth weights has led to the following conclusions. The total of 190 patients with congenital hemiplegia had a mean birth weight of 6.4 pounds, significantly lower than the mean of normal infants by 0.7 of a pound. Moreover, there were a significantly greater number of birth weights under 5 pounds in this series as compared with normals. There was no significant sex difference either between the means or in the incidence of premature or heavy birth weights in this series. Right hemiplegia births were significantly heavier than left by 0.5 of a pound. Although the ratio of left to right was 1:1 in premature births and in weights between 5 and 8 pounds, the ratio was nearby 1:2 in weights above 8 pounds. It is suggested that preponderance of L.O.A. deliveries may be responsible for the occurrence of more right than left hemiplegias in children of heavy birth weights. The incidence of premature and heavy birth weights was randomly distributed between convulsive and non-convulsive groups; the difference of 0.4 of a pound between the means in favor of the convulsive group was not significant. Birth weights in the educable and mental defective groups did not differ significantly. The frequency distribution of the total group and of most subgroups shows distinctly bimodal curves. The variance, or degree of dispersion, of birth weights is greater in this series of infants than in normal infants.

The observation of a universal shape regularity in earthquake frequency-magnitude distributions

1980 ◽  
Vol 70 (1) ◽  
pp. 349-362
Author(s):  
E. D. Bloom ◽  
R. C. Erdmann
Keyword(s):  
Statistical Analysis ◽  
Data Center ◽  
Data Bases ◽  
World Data ◽  
The Earth ◽  
Earthquake Frequency ◽  
Geological Diversity ◽  
Estimated Error ◽  
Frequency Magnitude ◽  
Terrestrial Data

abstract On performing a statistical analysis of the data available from both the National Geophysical and Solar Terrestrial Data Center (NGSDC) and other, smaller data bases, a convincing shape regularity was observed in the derived earthquake frequency-magnitude (f-M) distributions. The f-M distributions were obtained from sets of events originating within widely separated regions on the Earth. The regions have geological diversity and areas greater than 6 × 105 km2. To within estimated error, the shape of total world data agrees with similar plots of data subsets taken from these eight separate regions of the Earth.

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