{"id":19783494,"url":"https://github.com/krypten/playingcardsstatisticalanalysis","last_synced_at":"2026-05-12T11:42:48.448Z","repository":{"id":80314361,"uuid":"83695403","full_name":"krypten/PlayingCardsStatisticalAnalysis","owner":"krypten","description":"Statistical Analysis of Playing Cards (Descriptive Statistics: Final Project)","archived":false,"fork":false,"pushed_at":"2017-03-04T14:20:43.000Z","size":214,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-28T13:12:03.421Z","etag":null,"topics":["data-analysis","machine-learning","machinelearning","python","statistics","udacity"],"latest_commit_sha":null,"homepage":null,"language":"Python","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/krypten.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":"2017-03-02T15:49:30.000Z","updated_at":"2023-06-21T08:25:11.000Z","dependencies_parsed_at":null,"dependency_job_id":"7fa7018e-c51a-499f-ad7e-386ff581c6de","html_url":"https://github.com/krypten/PlayingCardsStatisticalAnalysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/krypten/PlayingCardsStatisticalAnalysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krypten%2FPlayingCardsStatisticalAnalysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krypten%2FPlayingCardsStatisticalAnalysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krypten%2FPlayingCardsStatisticalAnalysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krypten%2FPlayingCardsStatisticalAnalysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/krypten","download_url":"https://codeload.github.com/krypten/PlayingCardsStatisticalAnalysis/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krypten%2FPlayingCardsStatisticalAnalysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32937999,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-12T09:19:52.626Z","status":"ssl_error","status_checked_at":"2026-05-12T09:17:33.438Z","response_time":102,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 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":["data-analysis","machine-learning","machinelearning","python","statistics","udacity"],"created_at":"2024-11-12T06:08:30.290Z","updated_at":"2026-05-12T11:42:48.443Z","avatar_url":"https://github.com/krypten.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Statistical Analysis of Playing Cards (Descriptive Statistics: Final Project)\n\n## Overview\nIn this project, I have conducted an experiment dealing with drawing from a deck of playing cards and you can see the writeup containing my findings [here](#analyis-report-and-steps).\nThis experiment will require the use of a standard deck of playing cards. This is a deck of fifty-two cards divided into four suits (spades (♠), hearts (♥), diamonds (♦), and clubs (♣)), each suit containing thirteen cards (Ace, numbers 2-10, and face cards Jack, Queen, and King). You can use either a physical deck of cards for this experiment or you may use a virtual deck of cards such as that found on random.org (http://www.random.org/playing-cards/). In this task, I have assigned each card a value: The Ace takes a value of 1, numbered cards take the value printed on the card, and the Jack, Queen, and King each take a value of 10.\n\n## Analyis Report And Steps\n\n### Plotting a histogram of card values\nThe histogram depicts the relative frequencies of the card values.\n\n##### Frequency of the card value\n![histogram depicts the frequencies of the card values](https://github.com/krypten/PlayingCardsStatisticalAnalysis/blob/master/graph/card_frequency.png \"Histogram depicts the frequencies of the card values\")\n\n\n##### Relative Frequency of the card value\n![histogram depicts the relative frequencies of the card values](https://github.com/krypten/PlayingCardsStatisticalAnalysis/blob/master/graph/card_relative_frequency.png \"Histogram depicts the relative frequencies of the card values\")\n\n### Obtaining samples from a deck of cards\nI will get samples for the new distribution. Procedure: To obtain a single sample, shuffle my deck of cards and draw three cards from it. (I will be sampling from the deck without replacement.) Record the cards that I have drawn and the sum of the three cards’ values. Replace the drawn cards back into the deck and repeat this sampling procedure a total of at least thirty times.\n\n### Descriptive statistics regarding sample taken\nInclude at least two measures of central tendency and two measures of variability.\n\nMean :- \t\t\t23.375\u003cbr/\u003e\nMedian :- \t\t\t25.0\u003cbr/\u003e\nMode :- \t\t\t28\u003cbr/\u003e\nStandard Deviation :-\t\t5.94427245338\u003cbr/\u003e\nInterquartile range(IQR) :- \t9.25\u003cbr/\u003e\n\n### Plotting a histogram of sampled values\nThe histogram show sums for the sampled card.\n\n##### Frequency of the sampled distribution card values\n![histogram depicts the frequencies of the sampled distribution card values](https://github.com/krypten/PlayingCardsStatisticalAnalysis/blob/master/graph/sampled_frequency.png \"Histogram depicts the frequencies of the sampled distribution card values\")\n\n##### Normal Distribution of the sampled distribution card values\n![histogram depicts distribution of the sampled card values](https://github.com/krypten/PlayingCardsStatisticalAnalysis/blob/master/graph/sampled_normal_distribution.png \"Histogram depicts distribution of the sampled card values\")\n\n##### Questions\n\nQ: How are both the histograms different, and  why is this the case? \u003cbr/\u003e\nA: \n\n### Estimates based on the sampled distribution\nMake some estimates about values you will get on future draws.\u003cbr/\u003e\n\n\nQ. Within what range will you expect approximately 90% of your draw values to fall?\u003cbr/\u003e\nA. \n\nQ. What is the approximate probability that you will get a draw value of at least 20?\u003cbr/\u003e\nA.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrypten%2Fplayingcardsstatisticalanalysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkrypten%2Fplayingcardsstatisticalanalysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrypten%2Fplayingcardsstatisticalanalysis/lists"}