https://at-ceu.studyguide.timeedit.net/modules/ENVS5154?type=COREThis course provides a foundational understanding of statistical principles and their application in Environmental Science and Policy. Recognising that a robust grasp of quantitative methods is increasingly essential for evidence-based decision-making and research in environmental contexts, this module is designed for MSc students who may be new to formal statistical analysis or wish to solidify their existing quantitative methods knowledge. While some students may have prior exposure to statistics, this course adopts an accessible approach, utilising 'Learning Statistics with R' by Danielle Navarro - a textbook known for its clarity and practical, intuitive explanations tailored for beginners. The course will introduce core statistical concepts, progressing through descriptive statistics, foundational inferential tests, and ANOVA. Critically, students will gain hands-on experience using RStudio, a powerful and widely-used open-source statistical software, to conduct data analysis and create compelling visualisations relevant to environmental data.The overall aim of this course is to equip MSc students in Environmental Science and Policy with the fundamental quantitative literacy and practical skills necessary to critically engage with, interpret, and conduct fundamental statistical analyses of environmental data. By the end of this 6-session module, students will be able to:Understand and articulate core statistical concepts: Grasp the meaning of central tendency, variability, probability, hypothesis testing, and statistical significance.Apply appropriate statistical tests: Select and perform fundamental inferential statistical analyses, including t-tests and introductory ANOVA, relevant to common environmental research questions.Utilise RStudio for data handling and visualisation: Competently import, manipulate, and visualise environmental datasets using RStudio, producing clear and informative graphical representations.Interpret statistical results in an environmental context: Translate statistical outputs into meaningful conclusions and implications for environmental science and policy.Develop a foundational appreciation for experimental design: Understand the basic principles of quantitative research design and their importance in drawing valid environmental inferences.Text BookNavarro, D. (2018). Learning statistics with R: A tutorial for psychology students and other beginners (Version 0.6). University of New South Wales. https://learningstatisticswithr.com/