Statistical tools for climate and atmospheric science
Where to find open climate and atmospheric data and how to use it? Statistical tools for climate and atmospheric science introduces you to basic statistical methods for analyzing atmospheric and climate measurement data. During the course you are taught the basic concepts of statistical analysis and the most common explorative analysis methods for measurement data. After the course you are able to apply these methods on your own measurement data, prove statistically that the selected method is valid for the data in use and report the results in scientific paper or thesis.
Course learning goals:
After the course you know:
1. Basic terminology of statistical analysis
- variables
- scales
- distributions
- measures of center and variation
2. Most common methods of Descriptive and Inferential Statistics
3. The types of open atmospheric data and where to find them
4. How to conduct more advanced statistical analyses to your data
- regression, variance and covariance analysis
- linear and nonlinear models
- time series analysis
- multivariate methods
5. How to find the best analysis method for your data and prove the validity of the method
6. How to report the results in a scientific article
Course level: Master
Pre-requisities: The students need to be able to use some software capable of statistical computing, e.g. R, Python, SAS or Matlab and know the basics of probability calculus. Climate.now or similar knowledge is recommended. Scope: 5 ECTS
Available languages: ENG
Authors: University of Eastern Finland and University of Helsinki. The course is done in collaboration with the Nordic-Baltic network and Nordplus funding.
Where to study: University of Eastern Finland (course code 3352755), University of Helsinki (course code ATM308)
Link to study material: https://digicampus.fi/course/view.php?id=1392