Institute: Vállalkozásmenedzsment Intézet (1084 Budapest, Tavaszmezõ u. 15-17.) Credit: 3
Type of classes: Nappali Language: English Semester: 2018/19/1
Level: Technical Management BSc;
Responsible Teacher: Dr. Nagy Viktor Teacher(s): Dr. Nagy Viktor;
Consultations (total/week): Heti Lectures: 1 Practice lectures: 2 Labs: 0 Consultations: 0
Type of Exam: félévközi jegy
Aim of the subject: Upon completion of this course, students should understand the main concepts of statistics, use the basic jargon and be able to handle the tools and
formulas of descriptive statistics.
Requirements during the semester
(homeworks, essays,
excercises, teamworks,
part and final
oral/written exam etc.):
Students are required to attend all classes. Should a student accumulate 5 absences (excused and/or unexcused) out of 14 in the semester class,
he/she will not receive academic credits. Students are required to pass two tests. Students may get homework, which should be handed in until the
next lesson or presented in some minutes in the lectures.
Week of
Topics of lectures/practices
1. The field of Statistics. Descriptive and inferential Statistics. Data, information. Sources: primary and secondary. Qualitative and quantitative data. Direct observation, experiments, surveys.
2. Population, subpopulation, sample. Parameter, statistic. Measurement scales. Basic jargon. Discrete and continuous variables.
3. Comparison, ratios, harmonic, geometric, arithmetic, quadratic means.
4. Frequency distributions, classes, Lorenz curve, concentration.
5. Measures of central tendency, percentiles. Measures of dispersion, measures of relative position.
6. Graphing categorical and numerical data, charts.
7. Test 1
8. Contingency tables I. Measures of association.
9. Contingency tables II. Mixed relationship.
10. Contingency tables III. Correlation.
11. Comparison with the method of standardization.
12. Index numbers: simple indices, weighted aggregate indices: Laspeyres’ and Paasche’s indices, Fisher indices.
13. Test 2
14. Makeup exams
Type of evaluation,
repetition, calculation
of grade, etc.
Grade in this course are calculated numerically based on total points/percentages of the two tests although the instructor may raise or decrease it by one grade based on the active/inactive participation in classes or the level of the homework.
5 (excellent): 87 – 100 %
4 (good): 75 – 86 %
3 (satisfactory): 63 – 74 %
2 (pass): 51 – 62 %
1 (fail): 50 or less %
Should a student accumulate a total of 50 or less percentages, an additional chance is given to him/her to meet the requirements.
Type of evaluation,
repetition, calculation
of grade, etc.
in written
Compulsory literature: Louise Swift and Sally Piff: Quantitative Methods for Business, Management and Finance, Macmillan Education UK, 2014
Les Oakshott: Essential Quantitative Methods: For Business, Management and Finance. 6th Edition, Palgrave, 2016
Les Oakshott: Quantitative Methods. Palgrave, 2014
Robert Donnelly: The Complete Idiot`s Guide to Statistics. 2nd Edition, Alpha, 2007
Deborah J. Rumsey: Statistics For Dummies. 2nd Edition, Wiley, 2011
Suggested literature: David Freedman, Robert Pisani, Roger Purves: Statistics (4th Edition), W.W.Norton & Company Inc, 2007