---
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.

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