Comparing statistical methodologies for assessing yield variation across harvests in agricultural grasslands

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability. In agriculture, grasslands can play an important role in producing feed for animals and maintaining soil health in crop rotations. In recent years, mixing plant species with complementary traits have been proposed as a strategy to reduce the quantity of synthetic … Read more

Testing the relative importance of species diversity and nitrogen application on weed proportions in agricultural grasslands

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability. In agriculture, grasslands can play an important role in producing feed for animals and maintaining soil health in crop rotations. In recent years, mixing plant species with complementary traits have been proposed as a strategy to reduce the quantity of synthetic … Read more

Testing the relative importance of species diversity and nitrogen application on yields in agricultural grasslands

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability. In agriculture, grasslands can play an important role in producing feed for animals and maintaining soil health in crop rotations. In recent years, mixing plant species with complementary traits have been proposed as a strategy to reduce the quantity of synthetic … Read more

A comparison of analytical methods for assessing the relationship between species diversity and ecosystem outputs.

ELIGIBILITY: This project is for a student taking the online MSc in Statistics and Data Science. Biodiversity and ecosystem function studies investigate the relationship between species diversity and the outputs of an ecosystem. This project will compare two different analytical methods for analysing this relationship, one an ANOVA type analysis that categorises species diversity levels … Read more

Regression under Interference: Maximum Likelihood Approaches

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties co-depend on each other, meaning classical regression models that assume independent observations yield biased … Read more

Regression under Interference: Bayesian Approaches

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties co-depend on each other, meaning classical regression models that assume independent observations yield biased … Read more

Regression under Interference: Generalized Outcomes

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties are co-dependent, meaning that classical regression models assuming independent observations yield biased results. By … Read more

Regression under Interference: Missing Data

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties co-depend on each other, meaning classical regression models that assume independent observations yield biased … Read more

Regression under Interference: Dynamic Networks

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties co-depend on each other, meaning classical regression models that assume independent observations yield biased … Read more

Regression under Interference: Bipartite Netwprls

Project for MSc. in Statistics and Data Science The iglm package in R provides a unified statistical framework for modeling individual responses and social network structures simultaneously in connected populations. In real-world social and economic systems, individual behaviors and relationship ties are co-dependent, meaning classical regression models that assume independent observations yield biased results. Modeling … Read more