Topics in Applied Statistics

General

Course Contents

  • Empirical models of behavior analysis in management and economics: Simple and multiple linear models. Least squares method. Rate estimation. Properties of estimated coefficients, hypothesis testing, data variance estimation. Expected prices. R^2, F test. Applications using statistical packages.
  • Analysis of variance-covariance: Analysis of variance by a ranking criterion (factor)-Conditions for its application. Testing for equality of pairwise means (multiple comparisons of means) in one-criterion analysis of variance. Variation analysis according to two classification criteria (factors) – Conditions for its application. Testing for equality of pairwise means (multiple comparisons of means) in two-criteria analysis of variance. Choosing the best regression, forward, backward, stepwise methods, all possible regressions.
  • Categorical data analysis: Types of categorical variables, 2×2 correlation matrices, measures of correlation in 2×2 and (rxc) correlation matrices. Linear regression with categorical independent variables.
  • Nonparametric controls: Selection criteria and tradeoffs between parametric and nonparametric procedures. Hypothesis tests for 1 or 2 independent samples, hypothesis tests for 2 dependent samples, correlation tables. Basic non-parametric tests (the Wilcoxon test, the Mann-Whitney test, the Kruskal-Wallis test, etc.). Case studies and analysis of real data sets from various disciplines (Finance, Marketing, Social Sciences).
  • Indicators and Official Statistics: Introduction, indicators, indicators, simple and complex figures, base, change of base, selection of items, applied indexes in Greece, consumer price indexes, wholesale sales, deflation, National Accounts-Sources of Statistics, Statistics of employment, unemployment and wages, family budget surveys.

Educational Goals

The course aims to acquaint the students with specific topics of statistical analysis. Upon successful completion of the course, the student should be able to:

  • estimate models with more than one independent variable,
  • collect and analyze a set of quantitative or qualitative data,
  • perform qualitative and quantitative analysis of primary or secondary data using statistical packages,
  • estimate with the use of real statistical data any relationship that exists between these data,
  • manage a large amount of data to investigate and solve economic, demographic, business problems,
  • search and study the Greek and foreign literature regarding the topics they have been taught and to be able to write a comprehensive statistical paper.

General Skills

to be filled

Teaching Methods

  • Face to face.

Use of ICT means

  • Online guidance.
  • Slides Projection in the classroom.
  • Use of E-mail and onlne communication systems.
  • Use of e-learning system (moodle).

Teaching Organization

ActivitySemester workload
Lectures / Exercises39
Assignment(s)30
Personal Study56
Total125

Students Evaluation

to be filled

Recommended Bibliography

  1. Γναρδέλης, X. (2019). «Εφαρμοσμένη Στατιστική», Αθήνα: Εκδόσεις Παπαζήση.
  2. Δημητριάδης, E. (2017). «ΣΤΑΤΙΣΤΙΚΗ ΕΠΙΧΕΙΡΗΣΕΩΝ ΜΕ ΕΦΑΡΜΟΓΕΣ ΣΕ SPSS ΚΑΙ LISREL». Αθήνα: Εκδόσεις Κριτική.
  3. Τζωρτζόπουλος, Π. και Α. Λειβαδά (2012). «ΑΡΙΘΜΟΔΕΙΚΤΕΣ ΚΑΙ ΕΠΙΣΗΜΕΣ ΣΤΑΤΙΣΤΙΚΕΣ». Αθήνα: Εκδόσεις Οικονομικό Πανεπιστήμιο Αθηνών.
  4. Aczel, Α. και Sounderpandian (2013). «Στατιστική σκέψη στον κόσμο των επιχειρήσεων». Λευκωσία: Εκδόσεις για την ελληνική γλώσσα Broken Hill Publishers LTD.
  5. Field, A. (2016). «Η Διερεύνηση της Στατιστικής με τη Χρήση του SPSS της IBM». 1η Ελληνική έκδοση από την 4η Αγγλική. Αθήνα: Εκδόσεις Προπομπός.
  6. Keller, G. (2010). «Στατιστική για Οικονομία & Διοίκηση Επιχειρήσεων». 8η Έκδοση. Θεσσαλονίκη: Εκδόσεις Επίκεντρο.