151-0360/02 – Data analysis for diploma thesis (ADDP)

Gurantor departmentDepartment of Mathematical Methods in EconomicsCredits4
Subject guarantorprof. RNDr. Dana Šalounová, Ph.D.Subject version guarantorprof. RNDr. Dana Šalounová, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
FRI02 doc. Ing. Václav Friedrich, Ph.D.
FUN01 Mgr. Taťána Funioková, Ph.D.
POM68 RNDr. Marek Pomp, Ph.D.
S1A20 prof. RNDr. Dana Šalounová, Ph.D.
SED02 doc. Ing. Petr Seďa, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+2

Subject aims expressed by acquired skills and competences

Students will be able to create and modify datasets in SPSS or Excel, analyse them, interpret and present outcomes.

Teaching methods

Other activities


The aim of the subject is to acquaint students with tools of Excel or statistical software SPSS for analysis both numeric and non-numeric data. The choise of methods is oriented to data processing from marketing and sociological research needed for master's thesis. The subject is based on knowledge from the subject Statistika A and Statisitka B. Used software: IBM SPSS, MS Excel.The subject doesn't deal with analysis of time series.

Compulsory literature:

ANDERSON, David Ray, Dennis J. SWEENEY a Thomas Arthur WILLIAMS. Modern business statistics with Microsoft Office Excel. 5th ed. Stamford: Cengage Learning, c2015. ISBN 978-1-305-08218-2.

Recommended literature:

NORUŠIS, Marija. IBM SPSS Statistics 19 Guide to Data Analysis. Pearson 2012, ISBN-10: 0321748417, ISBN-13: 9780321748416.

Way of continuous check of knowledge in the course of semester

Practical excercises.


Other requirements

Like all the other students.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Design of research - sample methods, research hypothesis, sample size. 2. Data collections, creating a data file and entering data in SPSS, describing data sets, missing data, modyfying a data file, transforming variables. 3. Descriptive statistics, exploratory analysis, tables, graphs. 4. Principle of table and graphs creating with respect to their presentation. 5. Hypothesis testing on probability distribution. 6. Tests of independence of nominal variables. 7. Tests of independence of continuous variable, correlation, regression. 8. Comparing groups, independent samples, paired samples. 9. One-sided dependence, logistic regression. 10. Output processing, pivoting tables, editing charts and graphs, exporting of outputs to another programs.

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit Credit   3
        Samostatná práce Other task type   2
Mandatory attendence participation: tutorial 100 %.

Show history

Conditions for subject completion and attendance at the exercises within ISP: 50 %.

Show history

Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2023/2024 (N0414A050001) Marketing and Business P Czech Ostrava 2 Choice-compulsory type B study plan
2022/2023 (N0488A050004) Finance and Accounting (S02) Accounting and Taxes P Czech Ostrava 1 Compulsory study plan
2021/2022 (N0488A050004) Finance and Accounting (S02) Accounting and Taxes P Czech Ostrava 1 Compulsory study plan
2020/2021 (N0488A050004) Finance and Accounting (S02) Accounting and Taxes P Czech Ostrava 1 Compulsory study plan
2019/2020 (N0488A050004) Finance and Accounting (S02) Accounting and Taxes P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
Subject block without study plan - EKF - P - cs 2023/2024 Full-time Czech Optional EKF - Faculty of Economics stu. block

Assessment of instruction

2022/2023 Winter
2021/2022 Winter
2020/2021 Winter
2019/2020 Winter