Institute: Vállalkozásmenedzsment Intézet (1084 Budapest, Tavaszmezõ u. 15-17.) Credit: 4
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: 2 Practice lectures: 2 Labs: 0 Consultations: 0
 
Type of Exam: vizsga
 
Aim of the subject: Upon completion of this course, students should understand the main jargon of Statistics, be able to collect, graph, and critique data, use confidence
intervals and hypothesis test, analyze the data with correlation and regression.
Requirements during the semester
(homeworks, essays,
excercises, teamworks,
presentations,
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 may not receive academic credits.
Two tests.
Should a student accumulate 50 or less points/percentages in the two tests, an additional chance is given to him/her to meet the requirements, as
the prerequisite for the exam.
 
Week of
semester
Topics of lectures/practices
1. The Field of Statistics. Descriptive and Inferential Statistics. Data: Direct Observation, Experiments, Surveys. Measurement Scales. Basic Jargon.
2. Institutions (UN, OECD, EUROSTAT), Stiglitz-Report, Vision 2020.
3. National Accounts.
4. Frequency distributions. Measures of Central Tendency. Measures of dispersion, Measures of Relative Position.
5. Index Numbers.
6. Graphing Categorical and Numerical Data, Charts.
7. Random variable. Binomial Distribution, Normal Distribution, t-Distribution.
8. Sampling Distributions and Central Limit Theorem.
9. Confidence Intervals.
10. Hypothesis Testing (with One Sample).
11. Hypothesis Testing (with Two Samples).
12. Two-way Tables, Checking for Independence.
13. Correlation and Regression.
14. Time Series Analysis.
 
Type of evaluation,
repetition, calculation
of grade, etc.
Based on the two tests .
Grades in this course are calculated numerically based on total points/percentages of the two tests or the exam.
5 (Exellent): 87 – 100 %
4 (good): 75 – 86 %
3 (satisfactory): 63 – 74 %
2 (pass): 51 – 62 %
1 (fail): 50 or less %
Type of evaluation,
repetition, calculation
of grade, etc.
Written examination.
 
Compulsory literature: David Freedman, Robert Pisani, Roger Purves: Statistics (4th Edition), W.W.Norton & Company Inc, 2007
Suggested 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
Deborah J. Rumsey: Statistics II for Dummies. Wiley, 2009