Begin Courses with Data Analysis Using SPS Statistical Processing System

1986 ◽  
Vol 4 (3) ◽  
pp. 375-378
Author(s):  
Kenneth Hinze
Keyword(s):  
Data Analysis ◽  
Processing System ◽  
Statistical Processing

Expert survey and analysis of the results

2019 ◽  
Vol 85 (7) ◽  
pp. 73-82
Author(s):  
Vladimir O. Tolcheev
Keyword(s):  
Data Analysis ◽  
Research University ◽  
Statistical Processing ◽  
Educational Process ◽  
Expert Survey ◽  
Educational Modules ◽  
Training Modules ◽  
Engineering Institute ◽  
Good Agreement ◽  
Statistical Criteria

The issues of organizing an expert survey and carrying out statistical processing and analysis of the results are considered. The experts are the fifth-year students undergoing training at the Department of Management and Informatics «Moscow Power Engineering Institute» of the National Research University. The goal of the survey is revealing the disciplines that are most useful for employment in their specialty. We discuss the special features of the survey and a concept of «work in the specialty», with due regard for statistical reliability of the results. Data of written questionnaire gained in 2018 were processed and analyzed using cluster analysis (construction of dendrograms and application of the K-means method) and non-parametric statistical criteria (Friedman and Mann – Whitney – Wilcoxon). Data processing is implemented in the program STATISTICA. The analysis is carried out to reveal significant differences between the educational courses and assess the degree of consistency of the respondents to divide them into clusters that unite the students with similar judgments. Data analysis revealed that experts’ estimates in 2018 are in fairly good agreement with the estimates of previous studies; among the respondents there are three coalitions corresponding to the training modules «Software», «Management Theory», «Data Analysis»; the overall consistency of students in the two groups is very low (and, on the contrary, high in the identified clusters); grades are homogeneous and do not depend on training groups (and employment – unemployment of the respondents). The obtained results allow us to address a number of important questions regarding the ways of improving the educational process, e.g., to optimize yearly course hours for different educational modules.

scholarly journals Statistical processing system for the public use samples

1973 ◽  
Author(s):  
M. L. Levin ◽  
R. E. Mellen ◽  
N. B. Gove ◽  
W. B. Malthouse
Keyword(s):  
Processing System ◽  
Statistical Processing ◽  
The Public

scholarly journals Some Problems in Teaching the Methods of Statistical Data Analysis and Opportunities of Modern Information Technologies for their Solution

2019 ◽  
pp. 94-99
Author(s):  
A. A. Kovalev ◽  
V. A. Ignatenko ◽  
A. A. Yadchenko
Keyword(s):  
Data Analysis ◽  
Data Processing ◽  
Information Technologies ◽  
Statistical Data ◽  
Statistical Processing ◽  
Statistical Data Analysis ◽  
Statistical Parameters ◽  
Core Subjects ◽  
Planning Methods ◽  
The University

The problems in teaching the methods of statistical data analysis in evidencebased medicine place high demands on their application. The rigor of the approach requires extensive knowledge in both the direct professional sphere and in areas of knowledge that go far beyond the limits of medicine. It is not enough to simply type groups for the study or calculate average values and draw some conclusions based on this. It is important to recruit groups and evaluate the statistical parameters of the obtained results correctly. Moreover, it is requisite to know the purpose of the research, formulate the appropriate hypotheses even before the beginning of the experiment [1] or data collection, and not to invent them during the analysis of an array of heterogeneous numbers and names when writing articles. The material of data processing presented at the level of schemes and algorithms in combination with the use of the appropriate programs is greatly simplified and, most importantly, streamlined. In this case, the subject of statistics is perceived not as something abstract, but as a complex component of the principles of evidencebased medicine, without detaching it from specialized training.The involvement of specialists of the core subjects of the university sharing the examples of studies using the statistical processing and planning methods into the training will make it possible to improve orientation in a variety of the existing statistical methods of data processing, as well as to understand the importance and relevance of the use of statistics in medical research.

Regional Competitiveness

2022 ◽  
pp. 150-170
Author(s):  
Miloš S. Krstić ◽  
Vladimir Radivojević
Keyword(s):  
Human Capital ◽  
Regression Analysis ◽  
Data Analysis ◽  
Comparative Analysis ◽  
Trade Openness ◽  
Statistical Processing ◽  
European Countries ◽  
Regional Competitiveness ◽  
Correlation And Regression Analysis ◽  
The Impact

The aim of the chapter was to model the impact of selected determinants (trade openness, human capital, entrepreneurship, and innovation) on regional competitiveness, as well as to propose future activities and measures required to be implemented to improve the competitive performance of the regions. The research was conducted on the sample of 18 regions in six European countries: Serbia, Croatia, Slovenia, Northern Macedonia, Montenegro, and Romania. The database was prepared, and the statistical processing was performed in SPSS. In this data analysis, the following methods were used: comparative analysis, correlation, and regression analysis. The results of the research showed that the impact of the determinants—import dependence, the number of pupils enrolled in secondary education, gross domestic expenditure on research and development, and the number of companies per 10,000 inhabitants on the competitiveness of the region—are (statistically) significant.

scholarly journals PENGENDALIAN KUALITAS PRODUK NPK PHONSKA DENGAN METODE STATISTICAL PROCESSING CONTROL PADA UNIT PRODUKSI 2A PT. PETROKIMIA GRESIK.

MANAJERIAL ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 75
Author(s):  
Abdurrahman Faris Indriya Himawan ◽  
Muhammad Abidhin Al Habtsi
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Data Collection ◽  
Control Method ◽  
Statistical Processing ◽  
Study Data ◽  
Analysis Techniques ◽  
Npk Fertilizer ◽  
Processing Control

This study aims to determine the quality control of Phonska NPK fertilizer using Statistical Processing Control method. Statistical Processing Control to analyze and identify quality deviations in Phonska NPK products. There were five people in this study. Data collection techniques using observation, interviews and documentation. Data analysis techniques using Statistical Processing Control. PT. Petrokimia Gresik has Phonska NPK fertilizer products whose production has deviations but can be overcome using the SPC method (Statistical Processing Control).

scholarly journals Allelic polymorphism of microsatelite DNA locі of egg chikens

2020 ◽  
pp. 22-27
Author(s):  
A.V. Shelyov ◽  
◽  
K.V. Kopylov ◽  
N.P. Prokopenko ◽  
S.S. Kramarenko ◽  
...  
Keyword(s):  
Data Analysis ◽  
International Society ◽  
Microsatellite Dna ◽  
Statistical Processing ◽  
Allelic Polymorphism ◽  
Specific Character ◽  
Allelic Variants ◽  
Mutation Model ◽  
Allelic Variability ◽  
Stepwise Mutation

The analysis of allelic polymorphism of five industrial egg crosses of chickens by five microsatellite DNA loci (ADL0268, MCW216, LEI0094, ADL0278, and MCW248) was carried out. DNA loci were chosen according to the recommendations of the International Society for Animal Genetics (ISAG). Based on the results of mathematical-statistical processing and data analysis, the spectra and frequencies of allelic variability, the peculiarities of allele pools, were identified, and unique alleles were identified. In general, the species Gallus gallus is characterized by a specific character of allelic spectra for all investigated microsatellite DNA loci (P <0.001). The highest rates of allelic variability were recorded in brown crosses "Lohmann brown" and "Hisex brown" (Na (LimNa)=(9.2 (5-17) and 7.4 (6-11), respectively). The studied crosses were characterized by a shift in allelic spectra towards a decrease in the fragment length. “Lohmann white” stands out among the birds of other crosses by high consolidation for individual alleles for all studied microsatellites (from ADL278114 – 0.343 and ADL268108 – 0.485 to LEI094259 – 0.720, MCW0248213 – 0.785 and MCW0216137 – 0.920). Unique alleles with the highest frequency were found in brown cross chickens, and in the “Hy-Line W-98” bird, they were not found. The number of unique alleles identified varied from 1 ("Hisex white") to 11 ("Lohmann brown"). Locus LEI094 turned out to be the most polymorphic in terms of the number of unique alleles – 10 such allelic variants were identified for it. No unique alleles were identified at the ADL0268 locus. The obtained estimates criterion χ2 of K. Pearson indicate significant differences in the frequency distribution of alleles for all studied loci. When using the MICROSATELLITE ANALYSER software, it was found that the nature of the variability of the studied microsatellite DNA loci in five industrial crosses of the egg chickens, both in the number of identified alleles and in the nature of their distribution, corresponded to the stepwise mutation model (SMM).

scholarly journals Methods of teaching educational data mining for pedagogical students

2019 ◽  
Vol 23 (3) ◽  
pp. 14-24
Author(s):  
E. A. Terbusheva
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Educational Data Mining ◽  
Statistical Processing ◽  
Educational Process ◽  
Middle Level ◽  
Training Tool ◽  
Research Competence ◽  
Level Data ◽  
The Government

The aim of the article is to discuss and argue teaching educational data mining for pedagogical stu-dents and to describe the methodical system of educational data mining teaching for students with a middle level of mathematical and IT disciplines, that contributes to the development of student’s research competence. The relevance of the study is determined by the requirements for the ability of higher education graduates to analyze information and perform research using modern methods and technologies that are mentioned in the educational standards and the government order. They are associated with an increasing amount of accumulated data in various fields and the cost of the knowledge extracted from data. Materials and methods. The article describes the author’s methodical system of educational data mining teaching, which was developed rely on: analysis of requirements and expectations to the re-search competence level, data analysis skills and modern education in general; comparison and analysis of the content of educational programs, books and courses on data mining and related dis-ciplines, generalization of pedagogical experience. The main aspects underlying the methodology: a form of flipped learning, a concentric (iterative) content structure, research teaching methods, a set of practical tasks for developing research competencies and Weka software for data mining as the main technical training tool for practical tasks implementation. The effectiveness of the developed methodological system was tested by the educational process monitoring, students questioning and statistical processing of questionnaires data. Results. The study shows the relevance of educational data mining teaching for students of peda-gogical universities, studying in mathematical and informational specialization. The use of the de-scribed methodic system for senior pedagogical students allows increasing the level of research competence of students and significantly developing the competence of data analysis. Conclusion. The described methodical system can used be partially or completely by teachers and methodologists for teaching data analysis at the modern level and development of research compe-tence of students with an average level of knowledge in mathematical and IT disciplines. 

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