Methods of Statistical Analysis in Atmospheric Sciences
| Title | Μέθοδοι Στατιστικής Ανάλυσης στις Ατμοσφαιρικές Επιστήμες / Methods of Statistical Analysis in Atmospheric Sciences |
| Code | NGMCM201Y |
| Faculty | Sciences |
| School | Geology |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Common | No |
| Status | Active |
| Course ID | 600025533 |
Programme of Study: PMS METEŌROLOGIA, KLIMATOLOGIA KAI ATMOSFAIRIKO PERIVALLON 2024-2029
Registered students: 11
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 2 | 1 | 6 |
| Academic Year | 2025 – 2026 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600281680
|
Course Type 2021
Specific Foundation
Mode of Delivery
- Face to face
- Distance learning
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600281680
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Students are not required to have taken any prerequisite course.
Learning Outcomes
Upon successful completion of this course, students will be able to:
Apply Descriptive Statistics:
Calculate and interpret measures of central tendency (e.g., mean, median, quartiles), dispersion (e.g., variance, standard deviation), and shape (e.g., skewness and kurtosis coefficients) for atmospheric data.
Create and analyze graphical representations of data (e.g., histograms, box plots, cumulative frequency diagrams) for effective visualization of atmospheric phenomena.
Understand and Utilize Theoretical Distributions and Stochastic Processes:
Describe the fundamental principles of probability and the concepts of random variables.
Identify and apply the properties of basic theoretical distributions (e.g., Bernoulli, Binomial, Poisson, Normal) and Markov chains to problems in atmospheric sciences.
Analyze Atmospheric Time Series Data:
Apply descriptive and explanatory methods for pairs of time series (e.g., scatter plots, correlation, linear regression) to detect relationships between atmospheric variables.
Perform trend analyses on meteorological/climatological data using appropriate methods (e.g., Moving Average, Cumulative Differences, T-test, Mann-Kendall) and identify abrupt climatic changes.
Apply Statistical Inference and Hypothesis Testing:
Formulate and test statistical hypotheses, including homogeneity tests (e.g., Alexandersson test, Bartlett's test, Double Mass Curve method), using appropriate coefficients of determination.
Implement Advanced Multivariate Methods:
Utilize and interpret the results from multivariate data analysis methods, such as Principal Component Analysis (PCA), Canonical Correlation Analysis, and Cluster analysis, to understand complex atmospheric systems.
Evaluate Climate Models:
Apply methods for the estimation and evaluation of climate models using appropriate tools (e.g., ROC Curves, Taylor Diagrams) for validating and comparing predictions.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Work in teams
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introductory concepts and Descriptive Statistics. Statistical Variables – Measures of Central Tendency (mean, median, quartiles, etc.) – Measures of Dispersion (variance, standard deviation, etc.) – Measures of Shape (skewness and kurtosis coefficients). Methods of graphical representation and their explanation (charts, histograms, box plots, cumulative frequency diagrams). Basic principles of probability. Random Variables. Basic Theoretical Distributions and Stochastic Processes (Bernoulli Distribution, Binomial Distribution, Poisson Distribution, Hypergeometric Distribution, Normal Distribution N(μ, σ²) – Gauss Distribution, Geometric Distribution, Negative Binomial Distribution (Polya), Markov Chains (order k)). Descriptive and explanatory methods for pairs of time series (scatter plots, correlation, correlation coefficients, linear regression, covariance). Introduction to Statistical Hypothesis Theory (hypothesis testing, statistical hypothesis determination coefficients) – Homogeneity Hypothesis Tests – Alexandersson Homogeneity Test, Double Cumulative Curve Method, Bartlett’s Test. Trends in time series of meteorological – climatological data, Variations, Abrupt climate changes, Moving Average, Cumulative Differences, T-test, Mann Kendall. Multivariate data analysis methods: Principal Component Analysis, Canonical Correlation Analysis, Cluster Analysis. Methods for estimating and evaluating climate models (ROC Curves – Taylor Diagrams).
Keywords
Atmospheric sciences, statistics, climatology, evaluation, time-series analysis
Educational Material Types
- Notes
- Slide presentations
- Interactive excersises
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
In the context of the "Statistical Analysis Methods in Atmospheric Sciences" course, Information and Communication Technologies (ICT) are extensively utilized to enhance the learning process. Specifically, teaching is supported by modern learning management platforms (e.g., elearning or the equivalent AUTh platform) for posting material (lectures, notes, supplementary resources) and organizing assignments. Communication with students is facilitated via email and the platform's integrated discussion tools, ensuring immediate feedback and interaction. Furthermore, ICT forms an integral part of student assessment, as it's used for both submitting and grading assignments, as well as for conducting practical exercises with specialized statistical software (e.g., R or Python), which is a central pillar of the course.
Student Assessment
Student Assessment methods
- Written Exam with Extended Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
- Oral Exams (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
- Report (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Εξειδικευμένες διαφάνιες καθώς και δημοσιευμένες επιστημονικές εργασίες στην ύλη του κάθε μαθήματος.
Additional bibliography for study
Statistical Methods in the Atmospheric Sciences. Daniel S. Wilks, Academic Press
Statistical Analysis in Climate Research, Hans von Storch and Francis W. Zwiers, Cambridge University Press
Στατιστική με SPSS, Ζαφειροπουλος και Μυλωνάς, Εκδόσεις Τζόλα
Last Update
10-06-2025
