*LO Learning Outcomes

Hungarian: Statisztika I. Course title: Code: GT_AGMNE006 English: Statistics I.

Faculty of Economics and Business, Department of Research Methodology and Institute: Statistics Prerequisites: Statistics I. Code: GT_AGMNE006 Classes per week Type Requirement Credit Language of instruction: Lecture(s) Seminar(s) X per week 2 per week 2 oral exam 5 English

Responsible instructor name: Prof. Dr. Péter Balogh post professor Instructor name: János Szenderák post Course goals: The course introduces the basic statistical concepts and covers the procedures most frequently used in the descriptive analysis of cross-sectional and time-series data. The focus will be mainly put on the computation and interpretation of the most widely used statistical measures and some basic economic indicators that have importance in the socio-economic decision making process.

Course content , topics: The basic concepts of statistics; descriptive statistics: analysis of quantitative variables; stochastic relationships, graphical methods; sampling; estimation theory, point and interval estimation, basics of hypothesis tests.

Learning methods: During the seminars we solve exercises of the book using SPSS for getting the solutions. Attending the lectures and the seminars are compulsory. Assessment: The overall course grade will be based on the working on practices and the final computer exams. Compulsory readings: Anderson, Sweeney, Williams, Freeman and Shoesmith: Statistics for Business and Economics, Second edition, Cengage Learning EMEA, 2010. UK, 928. p. ISBN: 1408018101 Howitt, D. – Cramer D.: Introduction to Statistics in Psychology, 6/E Pearson, Harlow. 2014. 744. p. ISBN-13: 9781292000749 Recommended readings: Field A.: Discovering Statistics Using SPSS (Introducing Statistical Methods), 4th Edition, SAGE Publications Ltd., London, 2013. 915. p. ISBN-13: 978-9351500827

1 Syllabus

Week Topics 1. The statistical concepts and sub-areas. Statistical basic concepts of the population, criteria, parameters, sample. The statistical work phases. LO: The basic concepts of statistics. Data collection and utilization methods, data sources. Statistical opportunities in the Excel spreadsheet program. Functions and procedures, basic statistical operations. 3. Sampling procedures, random sample, systematic error parameter. Databases. The criteria of a good database. Database design rules. LO: Independent and identically distributed samples, simple sample, stratified sample. Group of samples, non random sampling techniques, combined and artificial samples. Non- responses in the sample. Selection rate calculation. 5. Levels of measurement data. Definition of the data for the different scales of measurement. Data Representations. LO: Definition of the data for the different scales of measurement. Creating and interpreting charts. 7. Relative numbers. Correlations between the relative numbers LO: Distribution, coordination, comparative calculation of performance ratios. Determination of the intensity ratios. 9. Central indicators: median, mode, mean. LO: Calculation of central indicators at different levels of measurement variables. 11. Central values: arithmetic, geometric, harmonic, quadratic. Calculation of weighted averages. LO: Means (arithmetic mean and the main characteristics, other types of means and typical fields of application). 13. The measures of variability: standard deviation, variance, range, absolute, relative differences in coefficient of variation, the relative coefficient of variation. LO: Calculation of dispersion from the population and sample. 15. Measure of concentration, Lorenz curve. Herfindahl-Hirschman-index. Correlation between the concentration and dispersion. LO: The practice of concentration analysis. 17. Indices LO: Basics of the calculation of the value-, price- and volume indices. The Laspeyres and Paasche indexes. Index relationships. The Fisher's indices. 19. The normal distribution as a model. Distribution and density function. Skewness and kurtosis characterization. LO: Preparation of Normal Distribution. Analysis of density and distribution functions. Standardization. Calculation of skewness and kurtosis, practical interpretation. 21. Standard values and regularities of normal distribution. Tests of normal distribution. LO: Standard values and regularities of normal distribution. Tests of normal distribution. 23. One-sided asymmetrical and two-sided symmetrical probabilities. LO: One-sided asymmetrical and two-sided symmetrical probabilities. 25. Student's t-distribution. The standard error of the mean. Confidence interval. LO: Determination of standard error. Confidence intervals were calculated for different probabilities. Practical application of the confidence intervals. 27. Statistical hypothesis tests, non-parametric tests. Chi-square test. LO: Independence testing, fit testing, homogeneity test. Chi-square tests. *LO learning outcomes