Learning Outcomes
Upon completion of this course, students will be able to:
1) Explain fundamental ideas of Probability and Statistics and the theory behind the commonly used statistical techniques.
2) Apply suitable statistical techniques correctly for solving biological problems.
3) Analyze data using common statistical software and interpret outputs.
4) Prepare statistical reports and make presentations.
5) Communicate with a statistician.
Course Content (Syllabus)
Introduction to Biometry. Descriptive and Inferential Statistics. Confidence intervals. Parametric and non-Parametric statistical tests. Agricultural experimentation and introduction to Analysis of Variance (ANOVA). Introduction to linear models (general/mixed). Methodology for setting up and statistically analysing data coming from simple experiments (Completely Randomized Design, Randomized Complete Block Design, Latin Square Design, Balanced Lattice Design). Methodology for setting up and statistically analysing data coming from factorial experiments (with crossed and/or nested factor structure). Statistical analysis of data coming from split plot designs and designs with repeated measures. Statistical analysis of data coming from designs combined over locations and/or years. Multiple linear and non linear regression. Introduction to Multivariate-Multidimensional Data Analysis.. Statistical Analyses for categorical data. Contingency tests. Analysis of biological data with statistical software.
Keywords
Experimental designs, Analysis of Variance, Linear and non linear Regression, Multivariate Data Analysis, Statistical Software
Description
Web, Internet, Powerpoint, video, Excel, SPSS, educational software-tutorial, zoom,email.
Additional bibliography for study
1) Steel, R., Torrie, J. & Dickey, D. (1997). Principles and Procedures of Statistics: A Biometrical Approach. Third Edition. Singapore: McGraw-Hill Book Company.
2) Gomez, K. & Gomez, A. (1984). Statistical Procedures for Agricultural Research. Singapore: John Willey & Sons, Inc.
3) Zar, J. (1996). Biostatistical Analysis. New Jersey: Prentice-Hall International, Inc.
4) Μενεξές, Γ. & Οικονόμου, Α. (2002). Σφάλματα και Παρανοήσεις στους Στατιστικούς Ελέγχους Υποθέσεων: Υπέρβαση μέσω της Ανάλυσης Δεδομένων. Τετράδια Ανάλυσης Δεδομένων-Data Analysis Bulletin, 2, 52-64.
5) Μενεξές, Γ. (2007). Μια Δομημένη Προσέγγιση στην Πολυμεταβλητή Στατιστική Ανάλυση Βιολογικών, Περιβαλλοντικών, Κοινωνικών και Οικονομικών Δεδομένων. Στο Φυσικοί Πόροι, Περιβάλλον και Ανάπτυξη (σσ. 519-534). Επιμέλεια: Γ. Αραμπατζής και Σ. Πολύζος. Θεσσαλονίκη: Εκδόσεις Τζιόλα.
6) Μενεξές, Γ. (2013). Οδηγός Ανάλυσης Παραλλακτικότητας Δεδομένων Γεωργικών Πειραμάτων με Στατιστικά Πακέτα. Εκπαιδευτικές Σημειώσεις.