Publications by Bonnie Cooper
Introduction to Data in R
Language of Data Study types and cautionary tales Sampling strategies and experimental design Case study Introduction to Data in R DataCamp: Statistics with R Bonnie Cooper Notes from videos and exercises. This is a casual follow along to help me remember all the things and to serve as future reference. Language of Data library( openintro ) ...
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Correlation and Regression in R
Correlation and Regression inR DataCamp: Statistics with R Bonnie Cooper library( dplyr ) library( ggplot2 ) library( gridExtra ) library( openintro ) library( tidyverse ) library( UsingR ) library( broom ) Visualizing two variables Visualizing bivariate relationships both variables are numeric response variable: y = dependant variable expl...
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Intro2PsychophysicalMethods
intro to psychophysical methodsBonnie Cooper Psychophysical Methodology Psychophysics: quantifying a relationship between stimulus & perception Psychophysical Methodology Thresholds The Psychometric Function Methods for determining Thresholds Signal Detection Theory Weber's Law Revisit the Photopic Luminosity Function Thresholds threshold ...
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photometry
photometry & radiometryBonnie Cooper Concepts & Units Radiometry: measurements of light in the physical world Photometry: measurements of light in the perceived world Luminous & Radiometric Power Luminous Power Total percieved light power emitted from a light source Units: Lumens Radiometric Power: Total emitted radiant energy from a radia...
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Dealing with Missing Data in R
Dealing with Missing Data in R DataCamp: Statistics with R Bonnie Cooper library( dplyr ) library( ggplot2 ) library( gridExtra ) library( tidyverse ) library( naniar ) library( simputation ) Why care about missing data? Introduction to missing data “The best thing to do with missing data is to not have any.” -Gertrude M. Cox Working wi...
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Foundations of Probability in R
Foundations of Probability in R DataCamp: Statistics with R Bonnie Cooper library( dplyr ) library( ggplot2 ) library( gridExtra ) library( openintro ) library( tidyr ) library(hrbrthemes) The Binomial Distribution Flipping Coins in R Simulating a coin flip in R with rbinom( numdraws, numcoins, prob(1) ) #the rbinom() function: rbinom( 1,1,....
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Experimental Design in R
Experimental Design in R DataCamp: Statistics with R Bonnie Cooper library( dplyr ) library( ggplot2 ) library( gridExtra ) library( tidyverse ) library( broom ) library( pwr ) library( ggfortify ) library( haven ) library( simputation ) library( sampling ) library( agricolae ) library( naniar ) library( mice ) Introduction to Experimental De...
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A/B Testing in R
A/B Testing in R DataCamp: Statistics with R Bonnie Cooper library( dplyr ) library( ggplot2 ) library( gridExtra ) library( tidyverse ) library( lubridate ) library( scales ) library( powerMediation ) library( broom ) library( pwr ) library( gsDesign ) Mini case study in A/B Testing Into A/B testing is not something that is done just once. ...
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DATA621 Readings
DATA621: readings & suggested problems MARR: A Modern Approach to Regression with R LMR: Linear Models with R ELMR: Extending the Linear Model with R Readings in bold (#problems in parentheses) Week MARR LMR ELMR 1 1 (#1.1, 1.3, 1.4, 1.5) 1 2 2.1 (#2.1, 2.2) 2 (#2.4, 2.5) 3 2.2-2.7 (#2.3) 3-5,14 (#3.4, 4.5, 5.2, 14.2) 4 3 (#3.3, 3.8) 6-9 (...
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Linear Models with R
Introduction Estimation Inference Prediction Explanation Categorical Predictors Diagnostics Transformation Missing Data Problems with Predictors Model Selection Shrinkage Methods Linear Models with R by Julian Faraway notes by Bonnie Cooper The following are notes from readings in ‘Linear Models with R’ by Julian Faraway for the course DA...
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