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Environmental Science Data Analysis

This repository showcases my environmental science data analysis work completed as part of EVSC 445: Environmental Data Analysis at SFU. All assignments were developed using R and focus on applying statistical methods to real-world ecological and environmental datasets.

Course Overview

EVSC 445 focuses on statistical and data analysis techniques commonly used in environmental science. The course covers how to design effective sampling and experiments, as well as how to analyze and interpret quantitative data collected from environmental monitoring, assessment, and restoration projects. It also emphasizes developing practical skills in the R programming language for data exploration, analysis, and visualization.

Learning Goals

Through this course, I developed skills in:

  • Applying exploratory data analysis to environmental datasets
  • Designing studies and experiments while minimizing bias, confounding, and inefficiency
  • Understanding probability concepts and random variables
  • Interpreting sampling distributions
  • Building confidence intervals and performing hypothesis testing
  • Applying both parametric and non-parametric statistical methods
  • Performing simple and multiple linear regression analysis
  • Exploring advanced topics such as mixed effects models and related statistical approaches

Assignments

This repository contains the following independent analyses:

  • Western Sword Fern Analysis
  • Dewberry Correlation Analysis
  • Fern Height Regression Analysis
  • GLM Nest Cavity Poisson Analysis
  • Stratification Library Analysis

Each folder includes its own README with detailed methods, analysis, and results.

Tools Used

  • R programming language
  • RStudio
  • Statistical modeling and data visualization techniques

About

My environmental science data analyses R scripts for the course: EVSC 445: Environmental Data Analysis

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