Sampling and Probability - Learning Statistics: Concepts and Applications in R
Explore sampling, probability, and statistical tools for extracting key information from data. Learn about data collection, probabilistic reasoning, and practical applications of Bayes' Rule in everyday life.
Handling Coefficients for Modeling Collegiate Sports Expenditures
Explore collegiate sports expenditures using linear modeling and tidymodels, focusing on handling coefficients and intervals for insightful analysis of financial patterns.
Explore Changes in Art Over Time With Tidymodels
Analyze art trends in the Tate collection using tidymodels for regression modeling, text feature engineering, and model diagnostics to uncover insights on changing art media usage over time.
Linear Mixed Model in R with lme
Learn to implement Linear Mixed Models in R using lme(). Understand statistical modeling concepts, fixed and random effects, and interpret results for complex data relationships.
Understanding Predictive Modeling with R
Learn to create predictive models using R, covering key concepts, training techniques, and practical demonstrations. Gain insights into model selection and explore various applications in data analysis.
Linear Regression with One X-Variable - Lecture 21
Explore simple linear regression using R, learning its powerful applications and detailed implementation in data analysis.
Journey of a Woman in Science
Inspiring talk on navigating challenges and opportunities for women in scientific careers, offering insights and encouragement for aspiring female scientists.
Cosine Similarity - Introduction to Text Analytics with R
Explore cosine similarity in text analytics: its mathematical basis, application in document comparison, and effectiveness in feature engineering for R-based text analysis.
Singular Value Decomposition with R - Introduction to Text Analytics with R Part 8
Learn to perform truncated SVD, project TF-IDF vectors into semantic space, compare decision tree and random forest models, and explore random forest tuning using R packages like irlba and caret for text analytics.
Multiple Linear Regression: Model Building and Selection
Build and select multiple linear regression models through data loading, visualization, and iterative model refinement using R.
Statistical Models: Linking Data to Theory - Class 10
Explore statistical models linking data to theory in quantitative ecology. Learn from expert Diogo Melo about advanced techniques for analyzing ecological data and developing robust theoretical frameworks.
Statistical Models: Linking Data to Theory - Class 8
Explore statistical models linking data to theory in quantitative ecology. Learn advanced techniques for analyzing ecological data and developing robust theoretical frameworks.
Statistical Models: Linking Data to Theory - Class 6
Explore statistical models linking data to theory in quantitative ecology. Learn advanced techniques for analyzing ecological data and developing robust theoretical frameworks.
Statistical Models: Linking Data to Theory - Class 5
Explore statistical models linking ecological data to theory in this advanced quantitative ecology lecture by Paulo Inacio Prado.
Statistical Models: Linking Data to Theory - Class 4
Explore statistical models linking ecological data to theory, focusing on advanced techniques for quantitative analysis in ecology.
Statistical Models: Linking Data to Theory - Class 3
Explore statistical models linking data to theory in quantitative ecology. Learn from expert Andrea Sanchez-Tapia in this comprehensive lecture on advanced ecological analysis techniques.
Statistical Models: Linking Data to Theory - Class 2
Explore statistical models linking data to theory in quantitative ecology. Learn from expert Andrea Sanchez-Tapia in this comprehensive lecture on advanced ecological analysis techniques.
Statistical Models: Linking Data to Theory - Class 1
Explore statistical models in ecology, linking data to theory. Learn logistic growth, ecological studies, and probabilistic modeling techniques for quantitative analysis.
Structure Tutorial
Learn to use Structure software for population admixture analysis using SNP data. Covers data preparation, project setup, analysis execution, and result visualization with a goat genotype example.
Shinylive - Running R and Python Dashboards Without a Server Using Web Assembly
Master browser-based deployment of R and Python Shiny Dashboards using Web Assembly, eliminating server dependencies while maintaining interactive data visualization capabilities.
Bivariate Analysis in R
Learn bivariate analysis techniques in R, including t-tests, ANOVA, chi-square, correlations, and linear regression. Gain practical skills for data science and statistics using RStudio.