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

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

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

Lectures: Schedule of theory Introductions to Research, Basic Statistical Methods Descriptive statistics Forms of statistical data collection and data management Statistical process management Statistical process management Graphical representation Schedule of practice MS EXCEL For DATA Analysis MS EXCEL For DATA Analysis MS EXCEL For DATA Analysis (I. test) Statistical process management (Exercises) Statistical process management (Exercises) (II. test)

Számonkérés és értékelés

The course ends with a midterm grade, a grade can be given after obtaining the signature, the statement of which is: In the case of a total performance rated at 30-49% at the end of the semester, the midterm grade is insufficient, which can be improved by one more attempt. If the practical task is below 50%, it can be re-administered by the end of the week after the semester. If the midterm test(s) are below 50%, one more attempt may be made to improve it in the first two weeks of the exam period. These occasions shall be appointed on the basis of individual requests. In the case of dual students, these dates may only fall on exam days or outside the dual practice period (late afternoon, weekend). Based on the collected points in the semester the grades are determined with the following scale:            0- 49% – fail (1);           50- 62% – pass (2);           63- 74% – satisfactory (3);           75- 86% – good (4);           87-100% – excellent (5).

Irodalomjegyzék

Recommended literature Author(s) Year Title Publisher Morris H. DeGroot, Mark J. Schervish 2014 Probability and Statistics Pearson Education John A. Rice 2017 Mathematical Statistics and Data Analysis Cengaga Learning

Ajánlott irodalom

Sheldon Ross 2019 Statistical Data Analysis for Engineers Elsevier Inc.

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