School of Computer Science and Statistics
ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability or the online MSc in Statistics and Data Science. 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 … Read more
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
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
ELIGIBILITY: This project is for a student taking the online MSc in Statistics and Data Science or the MSc in Statistics and Sustainability. 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 … Read more
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
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
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
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
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
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