Subjects

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Applied PC Techniques - M321003

Title:	Aplikovaná výpočetní technika
Guaranteed by:	Department of Carbohydrates and Cereals (321)
Faculty:	Faculty of Food and Biochemical Technology
Actual:	from 2019
Semester:	winter
Points:	winter s.:3
E-Credits:	winter s.:3
Examination process:	winter s.:
Hours per week, examination:	winter s.:1/2, MC [HT]
Capacity:	15 / 15 (unknown)
Min. number of students:	unlimited
State of the course:	taught
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time
Level:
Note:	course can be enrolled in outside the study plan enabled for web enrollment

Guarantor:	Pour Vladimír Ing. CSc.
Interchangeability :	N321015

Examination dates Schedule

Annotation -

Students on simple examples get familiar with basic statistical concepts and basic statistical operations. The necessary mathematical operations are designed using programmed functions in Excel spreadsheet. Emphasis is placed on evaluating statistical conclusions from both the model and from actual operating data.

Last update: Hladíková Jana (18.01.2018)

Aim of the course -

Students will be able to:

master the basic statistical and probability concepts

assess the statistical ensemble using basic statistical characteristics

use statistical functions in MS Excel to process the data files

Last update: Hladíková Jana (18.01.2018)

Literature -

R:Excel Guide

R:STATISTICS Methods and Applications, Statsoft

Last update: Hladíková Jana (18.01.2018)

Teaching methods - Czech

Přednášky, cvičení, samostatné projekty

Závěrečný test

Last update: Hladíková Jana (18.01.2018)

Syllabus -

1. Parameters and sample

2. Second Analytical results, measurement errors

3. Testing results

4. Rating experimentally observed dependence

5. Regression, correlation, extrapolation and interpolation

6. Evaluation of granulometric spectra

7. Processing of statistical analyzes on computers I. (Excel)

8. Development of statistical analysis on computers II. (Excel)

9. Working with data files

10. The calculation of statistical characteristics

11. Regression methods I.

12. Regression methods II.

13. Graphical presentation of the results I.

14. Graphical presentation of results II.

Last update: Hladíková Jana (18.01.2018)

Learning resources -

Mathematics I

Chemical Engineering I

Last update: Hladíková Jana (18.01.2018)

Registration requirements -

None.

Last update: Hladíková Jana (18.01.2018)