{"id":21089071,"url":"https://github.com/touradbaba/data_analysis_with_r_specialization","last_synced_at":"2026-05-19T11:32:58.544Z","repository":{"id":254331103,"uuid":"846190008","full_name":"TouradBaba/Data_Analysis_with_R_Specialization","owner":"TouradBaba","description":"This repository includes assignments, and labs from the Data Analysis with R Specialization by Duke University on Coursera. It covers a range of topics in statistics and data analysis using R, including probability, inferential statistics, and regression modeling.","archived":false,"fork":false,"pushed_at":"2024-11-16T18:32:42.000Z","size":2697,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-14T06:11:34.854Z","etag":null,"topics":["coursera","inference","inferential-statistics","linear-regression","r","r-language","statistics"],"latest_commit_sha":null,"homepage":"https://www.coursera.org/specializations/statistics","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TouradBaba.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-08-22T17:47:59.000Z","updated_at":"2024-11-16T18:32:46.000Z","dependencies_parsed_at":"2024-08-22T21:04:54.568Z","dependency_job_id":"69b02f2e-0aa9-427f-ac4f-3cdf9a7d8692","html_url":"https://github.com/TouradBaba/Data_Analysis_with_R_Specialization","commit_stats":null,"previous_names":["touradbaba/data_analysis_with_r__specialization","touradbaba/data_analysis_with_r_specialization"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TouradBaba/Data_Analysis_with_R_Specialization","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TouradBaba%2FData_Analysis_with_R_Specialization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TouradBaba%2FData_Analysis_with_R_Specialization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TouradBaba%2FData_Analysis_with_R_Specialization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TouradBaba%2FData_Analysis_with_R_Specialization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TouradBaba","download_url":"https://codeload.github.com/TouradBaba/Data_Analysis_with_R_Specialization/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TouradBaba%2FData_Analysis_with_R_Specialization/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33214334,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-19T07:54:09.561Z","status":"ssl_error","status_checked_at":"2026-05-19T07:54:08.508Z","response_time":58,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["coursera","inference","inferential-statistics","linear-regression","r","r-language","statistics"],"created_at":"2024-11-19T21:23:00.016Z","updated_at":"2026-05-19T11:32:58.527Z","avatar_url":"https://github.com/TouradBaba.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Analysis with R Specialization\r\n\r\nThis repository contains labs, assignments, and project files for the [**Data Analysis with R Specialization**](https://www.coursera.org/specializations/statistics) on Coursera, offered by **Duke University**. The specialization consists of three courses that explore various topics in statistics and data analysis using R. Below is an overview of the repository's structure.\r\n\r\n## 1. Introduction to Probability and Data with R\r\nThis course introduces the basics of R, RStudio, data structures, and the foundations of probability and data analysis.\r\n\r\n### Labs\r\n- **Week 1: Intro to R and RStudio**  \r\n  Lab File: `Week-1-Lab-Intro_R_RStudio.rmd`  \r\n  This lab covers the basics of R and the RStudio interface.\r\n  \r\n- **Week 2: Introduction to Data**  \r\n  Lab File: `Week-2-Lab-Intro_to_Data.rmd`  \r\n  Introduction to working with datasets and basic data visualization.\r\n  \r\n- **Week 3: Probability**  \r\n  Lab File: `Week-3-Lab-Probabilty.rmd`  \r\n  Focuses on understanding probability concepts in data analysis.\r\n\r\n- **Week 4: Data Analysis Project**  \r\n  Lab File: `Week-4-Lab-Data_Analysis_Project.rmd`  \r\n  Capstone project that combines data exploration and probabilistic reasoning.\r\n\r\n### Data\r\n- **BRFSS 2013 Data**  \r\n  File: `brfss2013.rdata`  \r\n  Dataset used in The Data Analysis Project\r\n\r\n---\r\n\r\n## 2. Inferential Statistics\r\nThis course focuses on inferential techniques, including sampling distributions, confidence intervals, and hypothesis testing for numerical and categorical data.\r\n\r\n### Labs\r\n- **Week 1: Sampling Distributions**  \r\n  Lab File: `Week-1-Lab-sampling_distributions_Coursera.rmd`  \r\n  Introduction to the concept of sampling and its distributions.\r\n\r\n- **Week 2: Confidence Intervals**  \r\n  Lab File: `Week-2-Lab-confidence_intervals_Coursera.rmd`  \r\n  Covers the theory and application of confidence intervals.\r\n\r\n- **Week 3: Inference for Numerical Data**  \r\n  Lab File: `Week-3-Lab-inf_for_numerical_data_Coursera.rmd`  \r\n  Focuses on hypothesis testing for numerical data.\r\n\r\n- **Week 4: Inference for Categorical Data**  \r\n  Lab File: `Week-4-Lab-inf_for_categorical_data_Coursera.rmd`  \r\n  Extends inferential techniques to categorical data.\r\n\r\n- **Week 4: Statistical Inference Project**  \r\n  Lab File: `Week-4-stat_inf_project.rmd`  \r\n  Final project on hypothesis testing and inference.\r\n\r\n### Data\r\n- **GSS Data**  \r\n  File: `gss.rdata`  \r\n  General Social Survey dataset used in The Statistical Inference Project.\r\n\r\n---\r\n\r\n## 3. Linear Regression and Modeling\r\nThis course dives into modeling relationships between variables using linear regression, extending into multiple regression.\r\n\r\n### Labs\r\n- **Weeks 1 \u0026 2: Simple Regression and Scatterplots**  \r\n  Lab File: `Week-1\u00262-Lab-simple_regression_Coursera.rmd`  \r\n  Introduction to simple linear regression with a focus on visualizing relationships.\r\n\r\n- **Week 3: Multiple Regression**  \r\n  Lab File: `Week-3-Lab-multiple_regression_Coursera.rmd`  \r\n  Learn to model more complex relationships using multiple regression.\r\n\r\n- **Week 3: Regression Modeling Project**  \r\n  Lab File: `Week-3-reg_model_project.rmd`  \r\n  Final project on building and interpreting linear regression models.\r\n\r\n### Data\r\n- **Movies Data**  \r\n  File: `movies.rdata`  \r\n  Dataset used in The Regression Modeling Project.\r\n\r\n---\r\n\r\n## Repository Files\r\n- **.gitattributes**  \r\n  Git configuration file to handle file attributes.\r\n  \r\n- **.gitignore**  \r\n  Specifies files and directories to be ignored by Git.\r\n\r\n---\r\n\r\n## Usage Instructions\r\n\r\nTo get started with this repository, it is recommended to install **R** and **RStudio**. Additionally, make sure to install the following R packages:\r\n\r\n```r\r\nlibrary(statsr)\r\nlibrary(dplyr)\r\nlibrary(shiny)\r\nlibrary(ggplot2)\r\n```\r\n\r\n### Cloning the Repository\r\n\r\nClone this repository to your local machine using the following command:\r\n\r\n```bash\r\ngit clone https://github.com/TouradBaba/Data_Analysis_with_R_Specialization.git\r\n```\r\n\r\n### Running the R Markdown Files\r\n\r\nOnce the repository is cloned, you can run the R Markdown (`.rmd`) files in RStudio. Open the desired `.rmd` file and use the \"Knit\" button to generate the output document.\r\n\r\n---\r\n\r\n## Acknowledgments\r\n\r\nThis repository is based on the **Data Analysis with R Specialization** offered by **Duke University** on Coursera. All credit for the course content goes to the creators of the specialization.\r\n\r\nFor more details and to enroll in the specialization, visit the official course page:  \r\n[Data Analysis with R Specialization on Coursera](https://www.coursera.org/specializations/statistics).\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftouradbaba%2Fdata_analysis_with_r_specialization","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftouradbaba%2Fdata_analysis_with_r_specialization","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftouradbaba%2Fdata_analysis_with_r_specialization/lists"}