--- title: "educationR: A Comprehensive Collection of Educational Datasets" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{educationR: A Comprehensive Collection of Educational Datasets} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 10, fig.height = 6 ) ``` ```{r setup} library(educationR) library(ggplot2) library(dplyr) ``` # Introduction The `educationR` package provides a **comprehensive collection of educational datasets, focusing on various aspects of education such as student performance, learning methods, test scores, absenteeism, and other educational metrics**. This package is designed to serve as a resource for educational researchers, data analysts, and statisticians who wish to explore and analyze data in the field of education. The datasets in the `educationR` package have been carefully curated and are ready to use for your data analysis needs. ## Dataset Suffixes Each dataset in the `educationR` package comes with a suffix that indicates the type and format of the dataset. These suffixes help users quickly identify the structure of the data, such as: - `tbl_df`: A tibble (a modern version of a data frame in R) - `df`: A standard data frame - `table`: A table (used for contingency tables or cross-tabulations) ## Example Datasets Below are some examples of datasets included in the `educationR` package: - `Achieve_tbl_df`: A tibble containing math achievement test scores by gender. - `German_tbl_df`: A tibble documenting before-and-after German copying errors post-course. - `QuizPulse10_df`: A data frame comparing quiz scores with lecture pulse rates. - `UCBAdmissions_table`: A table documenting student admissions at UC Berkeley. ## Data Visualization with educationR data sets Here are a couple of examples of how to use `educationR` package datasets to create data visualizations related to educational matters: ### 1. Visualization of Math Achievement by Gender ```{r ggplot2_001} # Example: Visualizing math achievement by gender Achieve_tbl_df %>% ggplot(aes(x = gender, y = score)) + geom_boxplot() + labs(title = "Math Achievement by Gender", x = "Gender", y = "Achievement Score") + theme_minimal() ``` ### 2. Visualization of Quiz Scores vs. Lecture Pulse Rates ```{r ggplot2_002} # Example: Visualizing the relationship between quiz scores and lecture pulse rates QuizPulse10_df %>% ggplot(aes(x = Quiz, y = Lecture)) + geom_point(alpha = 0.6) + labs(title = "Quiz Scores vs. Lecture Pulse Rates", x = "Quiz Score", y = "Pulse Rate (beats per minute)") + theme_minimal() ``` ## Conclusion The `educationR` package provides a wealth of educational data for analysis. By using the dataset suffixes, users can quickly identify the type of data they are working with, ensuring a smooth analysis process. For more information on each dataset and further examples, please refer to the full package documentation.