Publications by Sebastien Parker

Tutorial 6 (252)

21.07.2024

Setting Up R for Analysis First, let’s install and load the necessary packages. This step ensures that we have all the tools we need for our analysis. Data Preparation and Exploration Let’s create a binary outcome variable for Clinton votes in the 2016 election: # Load the States data data(USStates) States <- USStates States$Clinton <- abs(as...

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Tutorial 5 (SOC252)

16.07.2024

Introduction This tutorial covers how to perform Multiple Linear Regression (MLR) and interactions in R, including how to produce and interpret regression tables using sjPlot. We’ll use two datasets to start: HappyPlanetIndex (for global data) and States (for US state-level data). Setting Up R for Analysis First, let’s install and load the nec...

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Tutorial 4 (SOC252)

11.07.2024

# List of packages packages <- c("tidyverse", "fst", "modelsummary", "broom", "sjPlot", "ggplot2", "car", "Lock5Data", "mosaic") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packages()[,"Package"])] if(length(new_packages)) install.packages(new_packages) # Load the ...

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Tutorial 3 (252)

10.07.2024

# List of packages packages <- c("tidyverse", "fst", "modelsummary", "viridis", "kableExtra", "flextable", "officer") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packages()[,"Package"])] if(length(new_packages)) install.packages(new_packages) # Load the packages la...

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Second Tutorial (252)

06.07.2024

Visualizing and Exploring First, let’s load the packages we will use. You can always add more as needed # List of packages packages <- c("tidyverse", "gapminder", "fst", "viridis", "ggridges", "modelsummary", "RColorBrewer", "PrettyCols") # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packa...

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First Tutorial (252)

03.07.2024

Introduction to R and Exploratory Data Analysis (EDA) Welcome future data analysts! R is a powerful tool for statistical analysis and data visualization. This comprehensive tutorial will guide you through the basics of R, with a focus on Exploratory Data Analysis (EDA), answering simple descriptive questions, and visualizing the results. Setting U...

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Research Report

13.04.2024

# List of packages packages <- c("tidyverse", "infer", "fst") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packages()[,"Package"])] if(length(new_packages)) install.packages(new_packages) # Load the packages lapply(packages, library, character.only = TRUE) ## ...

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Document

13.04.2024

###Setting up the Environment # List of packages packages <- c("tidyverse", "infer", "fst", "modelsummary", "effects", "survey", "MASS", "aod", "interactions", "kableExtra", "flextable", "scales", "marginaleffects","performance") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% in...

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Homework 4 -- Answer Key

02.04.2024

# List of packages packages <- c("tidyverse", "infer", "fst", "modelsummary", "broom") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packages()[,"Package"])] if(length(new_packages)) install.packages(new_packages) # Load the packages lapply(packages, library, charact...

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Homework 5 -- Answer Key

29.03.2024

packages <- c("tidyverse", "infer", "fst", "modelsummary", "effects", "survey", "MASS", "aod", "interactions", "kableExtra", "flextable", "scales", "performance") # add any you need here # Install packages if they aren't installed already new_packages <- packages[!(packages %in% installed.packages()[,"Package"])] if(length(new_packages)) install.p...

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