Content for the bologna project about digital learning tools: Quantitive Methods: Usefull Statistics title: "Quantitive Methods for Geographers" author: "MSc Global Change Geography" date: "Winter term 2019/2020"

Welcome to Quantitative Methods!

About Quantitative Methods

Quantitative Methods is one of the fundamental courses for students of the Master Global Change Geography of Humboldt University Berlin. It's goal is the ability to analyse different advanced statistical and mathematical approaches to the quantitative analysis of geo- and environmental data and the modelling of human-environment systems. This online-tool will guide you through the following topics, and teach you statistics basics in R.

Course contents

The course will cover the following topics:

• Introduction to environmental modelling in R
• Mathematical preliminaries
• Introduction to spatial statistics
• Parameter estimation & linear regression
• ANOVA
• ANCOVA, multiple linear regression, collinearity, over-parameterisation, model comparison
• Generalised Linear Models (logistic & log-linear)
• Principle Component Analysis (PCA)
• Multivariate ANOVA (MANOVA), Discriminant Function Analysis (DFA), measures of accuracy, confusion * matrix, ROC/AUC, cross-validation
• Cluster analysis (kmeans & hierarchical)
• Spatial autocorrelation
• Spatial Variance and Covariance, semi-variogram, Kriging
• Spatially adjusted regression
• Introduction to time series analysis

Reading Material

Alternatively, you may want to follow one of the numerous tutorials for R fundamentals. e.g., RStudio, DataCamp, UMC Utrecht. In case you want to look up R in context of modeling &statistics, the the R Book by Crowley might be also of interest.It is propably the most helpful ressource in addition to this course. For vizualizing your data: R Graphics Cookbook.

Get started!

Simply follow - an interactive session should open (after about 15 seconds). Then simply select the File you want to work on and dive right into it! (Start is 01) Each session is structured in a guiding session, which introduces new concepts and a Practice-mode, in which you can practice your learned knowledge. Please always do both, before proceeding to the next session. Additionally, we provide some usefull extra knowledge or practical Information, these are always marked with 00 and are no sessions.

01 Introduction to R

• How to use Jupyter Notebook in the Browser
• Why do we use R?

02 Basics: Vectors.

• Basics of programming in R
• Calculations and variables
• vectors and datatypes

03 Basics: Data Frames.

• Matrices
• Data frame
• Data Manipulation

04 Data Wrangling

• Load packages
• Visualization
• Tidy data
• Data wrangling

00 Set up your Local R

• Start with RStudio
• Install Packages

00 Useful Shortcuts for JupyterNotebook

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