Kurzus nemzetközi vendég- és részidős hallgatóknak

Kar

Informatikai Kar

Szervezet

IK-SEK Savaria Műszaki Intézet

Kód

SBANGP3412EN

Cím

Technical and economical data analysis

Tervezett félév

Őszi

Meghirdetve

2024/25/1

ECTS

3

Nyelv

en

Leírás

The aim of the course is to introduce the methods of statistical data processing and analysis used in engineering practice. Data may come from quantitative reflection or measurement of economic and social processes (research, quality control, etc.), but the basic methods of processing and analysis are independent of the source. Using these advanced statistical methods, the information contained in the observed data set can be compressed, significant variables and effects can be detected, approximations can be made, and hypotheses can be decided by objective methods.

Oktatás célja

Aim of the subject The aim of the course is to introduce the methods of statistical data processing and analysis used in engineering practice. Data may come from quantitative reflection or measurement of economic and social processes (research, quality control, etc.), but the basic methods of processing and analysis are independent of the source. Using these advanced statistical methods, the information contained in the observed data set can be compressed, significant variables and effects can be detected, approximations can be made, and hypotheses can be decided by objective methods.

Tantárgy tartalma

Basic statistical description of data OLEP (On-line analytical processing) Association and correlations Supervised vs. unsupervised learning Basic concepts and methods Outlier analysis Introductions of data mining Basic statistical description of data Data processing OLEP (On-line analytical processing Data cube technology Association and correlations Advanced frequent pattern mining Supervised vs. unsupervised learning Advanced methods Basic concepts and methods week Cluster analysis, 2nd test 12. week Outlier analysis 13. week Summary

Számonkérés és értékelés

1. Attendance on lectures and practices (maximum 3 absences are allowed). 2. Submit all tests and assignments. 3. Course point value in the semester is 100 points. To accomplish the semester and get a possibility to the final exam is needed to acquire at least 50 points (50%). Points can be obtained as follows: a) Presentation: 1 x 20 points (20) b) Tests: 2 x 40 points (80) 4. The presentation can only be submitted to the lecturer. These can be only accepted with respect to the general content and form requirements. The home works can be corrected once.

Irodalomjegyzék

Morris H. DeGroot, Mark J. Schervish 2014 Probability and Statistics Pearson Education John A. Rice 2007 Mathematical Statistics and Data Analysis Cengaga Learning Sheldon Ross 2009 Statistical Data Analysis for Engineers Elsevier Inc.

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