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\|	\|	www.markhw.com Why and How to Model Conditional Variance, with an Application to My Letterboxd Data - Mark H. White II, PhD	2.7 parsecs away Travel
\|	\|	[AI summary] The blog post discusses modeling variance in data using the gamlss package in R, focusing on the user's film ratings over time. It highlights how the standard deviation of ratings increases with the release year of films, reflecting the user's movie selection habits. The analysis shows that older films have higher average ratings and lower variability, while newer films have lower average ratings and higher variability. The post emphasizes the importance of considering variance in social phenomena and provides practical examples using R for data visualization and statistical modeling.	2.7 parsecs away Travel
\|	\|	aosmith.rbind.io Simulate! Simulate! - Part 1: A linear model	3.5 parsecs away Travel
\|	\|	Where I discuss simulations, why I love them, and get started on a simulation series with a simple two-group linear model simulation.	3.5 parsecs away Travel
\|	\|	statsandr.com Multiple linear regression made simple - Stats and R	2.1 parsecs away Travel
\|	\|	Learn how to run multiple and simple linear regression in R, how to interpret the results and how to verify the conditions of application	2.1 parsecs away Travel
\|	\|	r-video-tutorial.blogspot.com R tutorial for Spatial Statistics: Power analysis and sample size calculation for Agriculture	22.1 parsecs away Travel
\|		Power analysis is extremely important in statistics since it allows us to calculate how many chances we have of obtaining realistic result...	22.1 parsecs away Travel