Course detail

Computer Evaluation of Experiments

FAST-CJ54Acad. year: 2013/2014

The preparation and evaluation of experiments, survey, the possibilities of utilization, the utilization of the programming system STATGRAPH. Handling with experimental data - making ready and conserving the data, corrections.
Describing statistics, frequency tables and histograms. Statistical analysis of one or two variables, probability distribution. Initial data analysis, quartile graphs, dispersion variance and covariance analysis. Interpolation of data in selected distribution, critical values. Distribution functions – calculation, graphic presentation.
Tests of distribution, quality control, smoothing of dependence. Simple and multiple, linear and non-linear regression. Filtering of remote measurements. Description of graphs and its print. Methods for proposal of an experiment and the experiment evaluation.
Estimation and testing of hypotheses.
Optimization task, methods of seeking the extremes, analysis and the formulation of the linear and quadratic programming task. Problems from the building practice of seeking the optimum- transport task, mixing problem, composition of raw material mixtures, grain distribution in the ground material.
The subject doesn’t contain a part with lectures, the exercise has a calculation character.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

prof. RNDr. Ing. Stanislav Šťastník, CSc. Ph.D.

Department

Institute of Technology of Building Materials and Components (THD)

Learning outcomes of the course unit

Upon completion of this course the student is able to use statistical methods to verify compliance with the declared performance requirements and physical properties of building materials. In view of this elective, the student must demonstrate that it is able to apply acquired knowledge / skills in practice. Simulation methods are represented by application software ANSYS. Students are familiar with using the computer system for applications in building thermal technology. To assess the achieved results are used measurement uncertainty.

Prerequisites

Basic Mathematics, basic work with PC

Co-requisites

In parallel with this subject the student in-depth knowledge about the technologies and properties of building materials under study. This increases the breadth of applications studied subject.

Planned learning activities and teaching methods

The course is taught through lectures, practical classes and self-study assignments. Attendance at lectures is optional, but attendance at classes is compulsory.

Assesment methods and criteria linked to learning outcomes

Students are assessed only in the exercise of this subject (no test). Evaluate the conditions for granting credit in compliance. It is a set of computational examples that student individually processed and submitted to the Head of exercise.
Criteria for meeting schedule:
- Development projects in the form of individual projects,
- Attendance,
- Written test.
By meeting these requirements, students will be enrolled credit for completing the course.

Course curriculum

1.Utilization of computer technique – PC – in building practice.
2.Fundamentals of work with data files.
3.Advanced work with data files – sorting and filtering of data.
4.Problems of data access, remote access to data and sharing of data files.
5.Utilization of PC technique in deciding processes.
6.Detailed acquainting with the medium MS Excel.
7.Work in the researcher’s table calculator Excel MS.
8.Fundamentals of data files statistic analysis.
9.Simple regression methods in MS Excel.The simplex method.The mixing task. The transport task.
10.Utilization for solution of simple mathematical problems in the MS Excel.

Work placements

Not applicable.

Aims

Statistic control of building materials physical properties, testing of statistic accordance of selected utility properties. Correlation analysis of parameters, utilization of statistic regularities for production quality control.Control of processing experimental control, simulation and static processesAdaptive control method, uncertainty in technological processes evaluation.

Specification of controlled education, way of implementation and compensation for absences

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Plesník, J., Dupačová, J., Vlach, M.: Lineárne programovanie. Alfa, Bratislava, 1990. neuvedeno. (SK)

Recommended reading

Duda, W. H.: Cement-Data-Book. Bauverlag Wiesbaden, 1977. neuvedeno. (EN)
Hušek, R., Lauber, J.: Simulační modely. SNTL/Alfa, 1987. neuvedeno. (CS)

Classification of course in study plans

  • Programme N-P-C-SI Master's

    branch M , 2. year of study, winter semester, elective

  • Programme N-P-E-SI Master's

    branch M , 2. year of study, winter semester, elective

  • Programme N-K-C-SI Master's

    branch M , 2. year of study, winter semester, elective

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

prof. RNDr. Ing. Stanislav Šťastník, CSc. Ph.D.

Syllabus

1.Utilization of computer technique – PC – in building practice.
2.Fundamentals of work with data files.
3.Advanced work with data files – sorting and filtering of data.
4.Problems of data access, remote access to data and sharing of data files.
5.Utilization of PC technique in deciding processes.
6.Detailed acquainting with the medium MS Excel.
7.Work in the researcher’s table calculator Excel MS.
8.Fundamentals of data files statistic analysis.
9.Simple regression methods in MS Excel.The simplex method.The mixing task. The transport task.
10.Utilization for solution of simple mathematical problems in the MS Excel.

Exercise

13 hours, compulsory

Teacher / Lecturer

prof. RNDr. Ing. Stanislav Šťastník, CSc. Ph.D.

Syllabus

1. use Řešitel / Solver in an MS Excel spreadsheet,
2. formulation of the computational model for use set of statistical functions in MS Excel,
3. construction division of discrete random variables,
4. construction division of continuous random variables, normal distribution function,
5. hypothesis testing, point and interval estimation,
6. Goodness use in the construction process,
7. quantification of risks and uncertainties credit,
8. determine the correlation dependence of two variables from practical measurements,
9. calculate the composition of cement raw mix called admissible solutions
10. monitoring compliance with student assignments, grant credits.