{
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  "Package": "MSMU",
  "Title": "Descriptive Statistics Functions for Numeric Data",
  "Version": "0.1.2",
  "Authors@R": "c(\nperson(given = \"Luke\", family = \"Papayoanou\", email = \"l.papayoanou@email.msmary.edu\", role = \"aut\"),\nperson(given = \"Jon\", family = \"McCurdy\", email= \"j.r.mccurdy@msmary.edu\", role =c(\"aut\", \"cre\"))\n)",
  "Description": "Provides fundamental functions for descriptive statistics,\nincluding MODE(), estimate_mode(), center_stats(),\nposition_stats(), pct(), spread_stats(), kurt(), skew(), and\nshape_stats(), which assist in summarizing the center, spread,\nand shape of numeric data. For more details, see McCurdy\n(2025), \"Introduction to Data Science with R\"\n<https://jonmccurdy.github.io/Introduction-to-Data-Science/>.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.3.2",
  "LazyData": "true",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-28 07:46:58 UTC",
    "User": "root"
  },
  "Author": "Luke Papayoanou [aut], Jon McCurdy [aut, cre]",
  "Maintainer": "Jon McCurdy <j.r.mccurdy@msmary.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-07-22 11:01:57 UTC",
  "RemoteUrl": "https://github.com/cran/MSMU",
  "RemoteRef": "HEAD",
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  "_type": "src",
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  "_published": "2026-05-28T07:49:23.351Z",
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    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
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    "MODE",
    "pct",
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    "skew",
    "spread_stats"
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      "title": "Professional baseball teams data",
      "object": "baseball_teams",
      "class": [
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      ],
      "fields": [
        "year",
        "team_name",
        "games_played",
        "wins",
        "losses",
        "world_series",
        "runs_scored",
        "hits",
        "homeruns",
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        "SRS",
        "SOS",
        "Points.Scored",
        "Points.Allowed",
        "FG.",
        "X3P.",
        "FT.",
        "Rebounds",
        "AST",
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      "fields": [
        "Gender",
        "Toy_Count",
        "Chores_Completed",
        "Favorite_Color",
        "Helping_Hand",
        "Complaints_Received",
        "Tantrum_Count",
        "Rule_Breaks",
        "Sharing_Behavior",
        "Hours_of_Sleep",
        "Screen_Time",
        "School_Grade",
        "Parent_Presence",
        "Greed_Score",
        "Outcome"
      ],
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    },
    {
      "name": "class_demographics",
      "title": "Class demographics",
      "object": "class_demographics",
      "class": [
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      ],
      "fields": [
        "names",
        "ages",
        "state",
        "year",
        "majors",
        "sport"
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        "Region",
        "Accept",
        "Enroll",
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        "Top25perc",
        "F.Undergrad",
        "P.Undergrad",
        "Outstate",
        "Room.Board",
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        "Grad.Rate"
      ],
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        "name",
        "fips",
        "pop",
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        "median_age",
        "age_over_18",
        "age_over_65",
        "hs_grad",
        "bachelors",
        "white",
        "black",
        "hispanic",
        "household_has_smartphone",
        "mean_household_income",
        "median_household_income",
        "unemployment_rate"
      ],
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      "table": true,
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    },
    {
      "name": "course_scores",
      "title": "Course scores data",
      "object": "course_scores",
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        "type",
        "Freshman_English",
        "Freshman_Math",
        "Sophomore_English",
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        "Senior_English",
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      ],
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        "ChestPain",
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        "AHD"
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        "Birth_weight"
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      "topics": [
        "baseball_teams"
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    },
    {
      "page": "basketball",
      "title": "College basketball data",
      "topics": [
        "basketball"
      ]
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    {
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      "title": "Summary of Central Tendency",
      "topics": [
        "center_stats"
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    },
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      "topics": [
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      "topics": [
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      "title": "Find the Mode of a Numeric Vector",
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        "MODE"
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      "title": "Mount St.Mary's dorm data",
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      "page": "MSMU",
      "title": "MSMU: Fundamental Data Functions Package",
      "topics": [
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        "MSMU"
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      "title": "Percent Within N Standard Deviations of the Mean",
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      "title": "Compute Sample Skewness",
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    }
  ]
}