Statistics practicum

TEACHERS IN CHARGE

STUDY, MODULE

Textile Technology and Engineering - graduate, Module Textile Design and Management
Textile Technology and Engineering - graduate, Module Textile Chemistry, Materials and Ecology
Textile Technology and Engineering - graduate, Module Clothing Engineering

SUMMARY

4 (2+0+2)

ECTS

KNOWLEDGE VERIFICATION

Seminar paper, oral exam

LECTURE TYPE

Lectures, seminars

EXPECTED LEARNING OUTCOMES

Student will be able to:

evaluate which is the appropriate graphical representation for the given statistical data in a statistical analysis software,
create a tabular presentation of statistical data and combine the appropriate statistical formulas for calculating parameters from descriptive statistics in a statistical analysis software,
determine which is the appropriate set of analysis tools in a statistical analysis software, and evaluate real data from textile technology by using different statistical methods,
critically reason which is the appropriate statistical test for data analysis in statistical analysis software and determine the correct statistical conclusion,
discuss an opinion on a concrete practical example from textile technology by using statistical methodology,
present the results of the statistical analysis and tests of measurement results by using a statistical analysis software.

SUBJECT CONTENT

Data collection and data management. Methods for describing qualitative and numerical data. Displaying basic statistical values. Population parameters (measures of central tendency, measures of dispersion, measures of asymmetry and roundness). Parametric model selection and data adjustment. Goodness of fit tests. Statistical tests about expectation, about variance, about distribution in general. Test of proportion. Regression analysis. Test of independence. Correlation test. Comparison of two populations. Comparison of multiple populations.

COURSE OBJECTIVES

Course objective is acquiring skills in application of statistical methods in textile technology by using statistical analysis software.

LITERATURE NECESSARY FOR COURSE

M. Benšić, N. Šuvak - Primijenjena statistika, Sveučilište J.J. Strossmayera, Odjel za matematiku, Osijek, 2013.
Ž. Pauše, Uvod u matematičku statistiku, Školska knjiga, Zagreb, 1993.

SUPPLEMENT LITERATURE

K. Krulić Himmelreich, K. Smoljak, Statistika, Fakultetski udžbenik u e-obliku, Zagreb, 2013.
McPherson, Applying and Interpreting Statistics, a comprehensive Guide, Springer-Verlag, Berlin, 2001.
A. Sen, M. Srivastava, Regression analysis: Theory, Methods, and Applications, Springer-Verlag, New York, 1990.
J.P. Marques de Sa, Applied Statistics using SPSS, Statistica, Matlab and R, Springer-Verlag, Berlin – Heidelberg, 2007