# Study-Unit Description

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CODE EMP2016

TITLE Statistics for Earth Systems Science

LEVEL 02 - Years 2, 3 in Modular Undergraduate Course

ECTS CREDITS 6

DEPARTMENT Environmental Management and Planning

DESCRIPTION This study-unit will introduce students to basic statistical concepts, with an emphasis on practical application. Throughout, theory and methods of analysis will be extensively illustrated with examples relating to Earth Systems and through use of appropriate software packages. Students will first be introduced to sampling design, sampling techniques and data collection methods to fundamental concepts relevant to statistical analysis, including probability, normality, confidence intervals and hypothesis tests.

After this, students will explore how to obtain graphical and numerical descriptions of data for continuous and categorical variables, obtained from observational or experimental studies. Students will also be introduced to inferential statistics, including statistical tests (Chi-squared test, t-tests, correlation tests, One-Way ANOVA test); as well as non-parametric alternatives. Students will also be introduced to linear regression and logistic regression analysis. A brief introduction and overview to R will also be provided.

Study-Unit Aims:

This study-unit aims to:

- Introduce students to the concept of sampling and enable them to understand the necessity of a careful sampling design;
- Equip students with the skills necessary to be able to conduct descriptive and inferential statistical analysis of given data sets;
- Make students aware of the important role of statistical analysis in research.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:

- Explain the elements of a reliable sampling design and strategy;
- Use statistics appropriately when conducting a study or experiment;
- Identify principles of good research design.

2. Skills:

By the end of the study-unit the student will be able to:

- Collect data in relation to an identified problem, propose a related appropriate mathematical/statistical technique/model, and use this technique/model to solve the problem;
- Test for reliability of data obtained;
- Select appropriate statistical techniques for data analysis;
- Apply mathematics and statistics to make predictions and inferences;
- Derive, analyze and assess relationships between variables.

Main Text/s and any supplementary readings:

- Madsen, B. (2011). Statistics for non-statisticians. Springer. ISBN: 978-3642176555.

STUDY-UNIT TYPE Lectures and Computer Lab Sessions

METHOD OF ASSESSMENT
 Assessment Component/s Assessment Due Resit Availability Weighting Analysis Task SEM1 Yes 25% Analysis Task SEM1 Yes 25% Analysis Task SEM1 Yes 25% Analysis Task SEM1 Yes 25%

LECTURER/S Liberato Camilleri (Co-ord.)