{"id":23012337,"url":"https://github.com/lmizner/codecademy_product_defects","last_synced_at":"2026-05-03T21:34:42.533Z","repository":{"id":140410058,"uuid":"547652951","full_name":"lmizner/codecademy_product_defects","owner":"lmizner","description":"Practicing rules of probability, set theory, and distributions","archived":false,"fork":false,"pushed_at":"2022-10-08T03:29:21.000Z","size":5,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-13T12:50:39.358Z","etag":null,"topics":["cdf","jupyter-notebook","numpy","pmf","ppf","python","rvs","scipy-stats"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/lmizner.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":"2022-10-08T03:27:56.000Z","updated_at":"2022-10-08T03:31:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"5b65ae42-bbde-42c7-a9ea-4b49a77ca58b","html_url":"https://github.com/lmizner/codecademy_product_defects","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/lmizner/codecademy_product_defects","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmizner%2Fcodecademy_product_defects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmizner%2Fcodecademy_product_defects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmizner%2Fcodecademy_product_defects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmizner%2Fcodecademy_product_defects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lmizner","download_url":"https://codeload.github.com/lmizner/codecademy_product_defects/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmizner%2Fcodecademy_product_defects/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32586187,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T06:36:36.687Z","status":"ssl_error","status_checked_at":"2026-05-03T06:36:09.306Z","response_time":103,"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":["cdf","jupyter-notebook","numpy","pmf","ppf","python","rvs","scipy-stats"],"created_at":"2024-12-15T10:13:39.186Z","updated_at":"2026-05-03T21:34:42.518Z","avatar_url":"https://github.com/lmizner.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# codecademy_product_defects\n\n### Detecting Product Defects with Probability\nYou are in charge of monitoring the number of defective products from a specific factory. You’ve been told that the number of defects on a given day follows the Poisson distribution with the rate parameter (lambda) equal to 7. You’re new here, so you want to get a feel for what it means to follow the Poisson(7) distribution. You remember that the Poisson distribution is special because the rate parameter represents the expected value of the distribution, so in this case, the expected value of the Poisson(7) distribution is 7 defects per day.\n\nYou will investigate certain attributes of the Poisson(7) distribution to get an intuition for how many defective objects you should expect to see in a given amount of time. You will also practice and apply what you know about the Poisson distribution on a practice data set that you will simulate yourself.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flmizner%2Fcodecademy_product_defects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flmizner%2Fcodecademy_product_defects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flmizner%2Fcodecademy_product_defects/lists"}