Download Module Title: Statistics

Module Title:
Statistics
Type of Module:
x
PC (Prescribed Core Module)
PS (Prescribed Stream Module)
ES (Elective Stream Module)
E (Elective Module)
Level of Module
Undergraduate
Year of Study
3rd
Semester
6th
Number of credits allocated
4.5
Name of lecturer / lecturers :
Vasilis Koutras
Description:
The first part of the course includes a review of basic concepts of probability theory and a short
introduction in Descriptive Statistics. The second part, presents the fundamental concepts of
statistics used to inference effectively on the characteristics of a population based on samples. A
random sample is taken from a population and based on this, estimators for the population’s
parameters are computed and their accuracy is examined. Additionally, the procedures used to
test hypotheses about a population are presented. To this direction, the course focuses on
estimation theory, confidence intervals, hypothesis testing, non-parametric test. Finally, the basic
concepts of linear regression are also presented.
Prerequisites:
None (student must be familiar with topics in Probability Theory)
Module Contents (Syllabus):
Week 1.
Week 2.
Week 3.
Week 4.
Week 5.
Week 6.
Week 7.
Week 8.
Week 9.
Week 10.
Week 11.
Week 12.
Introduction-Probability Theory, Distributions and moments-Exercises
Sample distributions, Student distribution, χ2 distribution, F distribution-Exercises
Sampling, Central Limit Theorem-Exercises
Descriptive statistics
Estimation, Unbiased Estimators (bias, consistency, adequacy, completeness)-Exercises
Estimator of minimum variance-Exercises
Maximum likelihood estimators-Exercises
Confidence intervals-Exercises
Hypothesis testing for the mean
Exercises in hypothesis testing for the mean
Hypothesis testing for binomial p, difference of means, variance-Exercises
Goodness of fit, Kolmogorov-Smirnov test-Exercises
Week 13. Correlation, Regression Analysis
Recommended Reading:
Α) Principal Reference:
[Option 1] Εισαγωγή στη Στατιστική, Τ. Παπαϊωάννου, Σ .Β. Λουκάς, Εκδόσεις Σταμούλη
Α.Ε., Κωδικός Βιβλίου στον Εύδοξο: 22745 (in greek)
[Option 2] Πιθανότητες και Στατιστική για Μηχανικούς, Γ. Ζιούτας,, Εκδόσεις "σοφία"
Ανώνυμη Εκδοτική & Εμπορική Εταιρεία, Κωδικός Βιβλίου στον Εύδοξο: 12656654
(in greek)
Β) Additional References:
1. Εισαγωγή στις πιθανότητες και τη στατιστική, Δαμιανού Χ., Χαραλαμπίδης Χ., Παπαδάκης
Ν., Εκδόσεις Συμμετρία, 2010 (in greek)
2. Πιθανότητες και Στατιστική, (Schaum's Outline of PROBABILITY AND STATISTICS),
Murray R. Spiegel, Μετάφραση: Σωτήριος Κ. Περσίδης (in greek)
3. Στατιστική, Υ. Κολυβά-Μαχαίρα, Ε. Μπόρα-Σέντα, Ζήτη (in greek)
4. Ανάλυση Δεδομένων με τη Βοήθεια Στατιστικών Πακέτων SPSS, Excel, S-Plus, Ν. Δ.
Σσάντας,
Φρ. Θ. Μωϋσιάδης, Ντ. Μπαγιάτης, Θ. Φατζηπαντελής,
Εκδόσεις Ζήτη,
Θεσσαλονίκη 1999. (in greek)
5. Introductory Statistics, S M. Ross, Second Edition,, Academic Press; 2 edition, 2005
6. Theoretical statistics, D. R. Cox, D. V. Hinkley, London:Chapman and Hall, New York, 1979.
7. Statistics: An Introduction using R, M. J. Crawley, Wiley; 1 edition, 2005.
8. Introduction to probability and statistics: principles and applications for engineering and
the computing sciences, J. S. Milton, Jesse C. Arnold, 3rd ed. New York :McGraw-Hill, 1995.
9. Introduction to statistical theory, Paul G. Hoel, Sidney C. Port, Charles J. Stone, Boston
:Houghton-Mifflin, 1971.
10. An Introduction to Statistics, G. Woodbury, Duxbury Press; 1 edition, 2001)
Teaching Methods:
Statistical Inference theory, examples and exercises. Lab in SPSS
Assessment Methods:
Final Exams = 20% + Assignment is SPSS = 20%
Language of Instruction:
Greek
Module Objective (preferably expressed in terms of learning outcomes and competences):
The aim of the course consists in introducing the basic concepts of Statistical Inference. These
concepts are prerequisites for future courses (Financial Econometrics, Forecasting and Applied
Statistical Techniques)
A successful student should be able to:
understand and use basic statistical concepts underlying the characteristics of a population
based on a random sample
compute and interpret confidence intervals for estimations
conduct hypothesis testing for the mean of a population, the binomial p, the difference
between the means of two population, the variance of a population
comprehend “non-parametric statistic” and conduct the appropriate tests
use linear regression to examine the relation between an independent and a dependent
variable, along with interpreting the results of regression