{"id":19785002,"url":"https://github.com/donghquinn/analye_hub_intro","last_synced_at":"2026-03-05T11:02:10.275Z","repository":{"id":260494897,"uuid":"881457214","full_name":"donghquinn/analye_hub_intro","owner":"donghquinn","description":"This is an introduction of Analyze Hub project","archived":false,"fork":false,"pushed_at":"2024-11-04T04:45:28.000Z","size":9734,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-28T13:23:31.368Z","etag":null,"topics":["analyze","project","statistics"],"latest_commit_sha":null,"homepage":"https://www.analyze-hub.com","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/donghquinn.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":"2024-10-31T15:57:41.000Z","updated_at":"2024-11-04T04:45:31.000Z","dependencies_parsed_at":"2024-10-31T17:18:11.666Z","dependency_job_id":"08f87aa9-40e5-4e55-8987-eebc8cc699e9","html_url":"https://github.com/donghquinn/analye_hub_intro","commit_stats":null,"previous_names":["donghquinn/analye_hub_intro"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/donghquinn/analye_hub_intro","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/donghquinn%2Fanalye_hub_intro","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/donghquinn%2Fanalye_hub_intro/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/donghquinn%2Fanalye_hub_intro/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/donghquinn%2Fanalye_hub_intro/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/donghquinn","download_url":"https://codeload.github.com/donghquinn/analye_hub_intro/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/donghquinn%2Fanalye_hub_intro/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30121059,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-05T10:44:24.758Z","status":"ssl_error","status_checked_at":"2026-03-05T10:44:15.079Z","response_time":93,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["analyze","project","statistics"],"created_at":"2024-11-12T06:13:16.996Z","updated_at":"2026-03-05T11:02:10.255Z","avatar_url":"https://github.com/donghquinn.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Statistical Analysis Web Program\n\n## Service Introduction\n\nThis web program offers various statistical analysis services. The main services currently provided are:\n\n1. **Descriptive Statistics**: Summarizes and describes basic features of the data. Calculates measures such as mean, median, and standard deviation to understand data distribution and characteristics.\n2. **T-Test**: \n   - **One-sample T-Test**: Tests if the mean of a single sample differs from a specific value.\n   - **Paired-sample T-Test**: Tests the mean difference between two related samples.\n   - **Independent-sample T-Test**: Tests the mean difference between two independent samples.\n3. **ANOVA**: \n   - **One-way ANOVA**: Tests mean differences among multiple groups.\n   - **Two-way ANOVA**: Tests effects of two independent variables and their interaction on a dependent variable.\n   - **Multivariate ANOVA (MANOVA)**: Tests mean differences among groups on multiple dependent variables simultaneously.\n4. **REGRESSION**: Models the relationship between an independent variable and a dependent variable through simple regression analysis.\n\n### Technology Stack\n\n- **Statistical Analysis Server**: Python FastAPI\n- **Backend**: Golang\n- **Frontend**: Next.js App Router\n\nWebsite: [https://www.analyze-hub.com](https://www.analyze-hub.com)\n\n**For the best experience, we recommend accessing the website on a desktop environment**\n\n### Demonstration Videos\n\n#### Paired-sample T-Test Demonstration\n![Paired-sample T-Test Demonstration](paired.mp4)\n\n#### Two-way ANOVA Demonstration\n![Two-way ANOVA Demonstration](twoway.mov)\n\n### TODO\n\n1. Currently, user registration/login is implemented using bcrypt and base64. We plan to introduce SSO (Single Sign-On) with providers like Google, Apple, and Kakao in the future.\n2. Implementing features to save analysis results as images or CSV files and generate textual summaries of the analysis results.\n\n# 통계 분석 웹 프로그램\n\n## 서비스 소개\n\n이 웹 프로그램은 다양한 통계 분석 서비스를 제공합니다. 현재 제공되는 주요 서비스는 다음과 같습니다:\n\n1. **기술통계분석**: 데이터의 기본적인 특성을 요약하고 설명합니다. 평균, 중앙값, 표준편차 등의 통계량을 계산하여 데이터의 분포와 특성을 파악합니다.\n2. **T-Test**: \n   - **일표본 통계분석**: 단일 표본의 평균이 특정 값과 다른지 검정합니다.\n   - **대응표본분석**: 두 관련 표본 간의 평균 차이를 검정합니다.\n   - **독립표본분석**: 두 독립된 표본 간의 평균 차이를 검정합니다.\n3. **ANOVA**: \n   - **일원분산분석**: 여러 그룹 간의 평균 차이를 검정합니다.\n   - **이원분산분석**: 두 개의 독립 변수와 그 상호작용이 종속 변수에 미치는 영향을 검정합니다.\n   - **다원분산분석(MANOVA)**: 여러 종속 변수에 대한 그룹 간의 평균 차이를 동시에 검정합니다.\n4. **REGRESSION**: 단순 회귀 분석을 통해 독립 변수와 종속 변수 간의 관계를 모델링합니다.\n\n### 사용된 기술 스택\n\n- **통계 분석 서버**: Python FastAPI\n- **백엔드**: Golang\n- **프론트엔드**: Next.js App Router\n\n웹사이트 주소: [https://www.analyze-hub.com](https://www.analyze-hub.com)\n\n**최적의 경험을 위해 데스크탑 환경에서 접속하는 것을 권장합니다**\n\n### 시연 영상\n\n#### 대응표본 검정 시연\n![대응표본 검정 시연](paired.mp4)\n\n#### 이원분산분석 시연\n![이원분산분석 시연](twoway.mov)\n\n### TODO\n\n1. 현재 회원가입/로그인은 bcrypt와 base64를 함께 사용해서 사용하고 있으며, 추후에 Google, Apple, Kakao 등의 SSO를 도입할 예정입니다.\n2. 분석 결과 이미지 / CSV 저장 및 분석 결과 텍스트 생성 기능을 구현할 예정입니다.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdonghquinn%2Fanalye_hub_intro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdonghquinn%2Fanalye_hub_intro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdonghquinn%2Fanalye_hub_intro/lists"}