Subject: APPLIED
STATISTICS
Prerequisites: Probability and
statistics, matrix algebra.
Aims of
the subject:
Principles
of statistical thinking and statistical inference. Understanding of some
statistical procedures, explanation the results of statistical evaluations.
Solving problems and examples from business world and marketing. Integration
theory and the use of statistical software packages (NCSS, SPSS Student
Version) with decision making procedures.
Subject
matter:
1. Estimating population values. Point and
confidence interval estimates for the population mean and population proportion
2. Hypothesis testing: definitions and steps,
3. Tests concerning population means (one-sample,
two-samples), F-test
4. Hypotheses about population proportions
5. Categorical variables. Contingency tables.
Chi-square test
6. Design of experiments and ANOVA
7. Simple linear regression, least square
method, inference for regression
8. Multiple regression: Assumptions, estimates,
inference for multiple regression
9. Analysing and forecasting time-series data.
Time series, description of their components. Trend analysis, forecasting
10. Seasonality and cyclical behaviour –
empirical estimates
11. Forecasting using smoothing methods. Exponential
smoothing methods
12. Introduction to multivariate
classification. General purpose and description of discriminant function
analysis
13. General purpose and description of cluster
analysis
Assessment
strategy and method:
Solving
exercises, written test, exam.
Indicative
reading:
1. Groebner D.F., et al: Business Statistics,
A Decision – Making Approach. Prentice Hall (2008, 2005, 2001)
2. McClave J.T., Benson P.G., Sincich T.:
Statistics for Business and Economics. Prentice Hall International,
3. Sincich T.: Business Statistics by Example.
Macmillan Publishing Company.