Planeshifter

Planeshifter

---
title: HELPrct
language: en-US
state: null
license: 'CC BY 4.0 [https://creativecommons.org/licenses/by/4.0]'
require:
  dataFile: 'https://isle.stat.cmu.edu/data-explorers_HELPrct.json'
  dataInfoFile: 'https://isle.stat.cmu.edu/data-explorers_HELPrct_info.json'
---

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<ol>
<li>The output below pertains to the participants in the Fast Food experiment. It reports summary statistics for the variable “dieting” by the respondent’s self-identified race. Variable “dieting” is coded as 1 if the respondent reported he/she was dieting, and 0 if the respondent reported no. From this table, calculate the probability that a randomly chosen participant in this experiment is dieting. Show the basis for your calculation and perform this calculation with relevant probabilities calculated to the thousandth (e.g, 0.342, 0.096, 0.004). (Note: You’ll observe that the top row constituing 22 respondents reports no race. Do not include this group in your calculation.) 

<Image src="https://isle.heinz.cmu.edu/95-796_Module3c_Q1.jpg" alt="Homework 2 Question 1 Image" />
</li>

<li>This problem concerns testing for COVID19 antibodies.
    Let:
        $C^{+}$ denote actually having COVID19 antibodies (i.e. “ground truth”) <br />
    $\tilde{C}^{+}$ denote not actually having COVID19 antibodies (i.e.

Planeshifter

// MODULES //

const fs = require( 'fs' );
const { join } = require( 'path' );


// VARIABLES //

const RECORDS = {};
const FLAGGED = {

Planeshifter

{
	"name": "Diabetes Treatment Data",
	"info": [
		"Diabetes, a metabolic disease affecting insulin production can be managable given proper treatment.",
		"In certain cases a diagnosis of diabetes is initially treated and controlled in a hospital setting.",
		"To better study the treatment patterns and outcomes, we have assembled a sample of ten years of",
		" clinical care at 130 U.S  hospitals for patients who were admitted with diabetes."
	],
	"variables": {
		"race": "Race of patient. One of \"Caucasian\", \"AfricanAmerican\", \"Hispanic\", \"Other\" or \"Asian\".",

Planeshifter

library(jsonlite)
library(readr)

diabetes <- readr::read_csv("diabetes.csv")
write( toJSON( diabetes, dataframe = "columns" ), "diabetes.json" )

Planeshifter

IDENTIFIED
{
  DATE: { missed: 792, hits: 4166, recall: 0.8402581686163776 },
  DOCTOR: { missed: 310, hits: 1575, recall: 0.8355437665782494 },
  PATIENT: { missed: 186, hits: 684, recall: 0.7862068965517242 },
  USERNAME: { missed: 0, hits: 92, recall: 1 },
  HOSPITAL: { missed: 62, hits: 712, recall: 0.9198966408268734 },
  STREET: { missed: 50, hits: 85, recall: 0.6296296296296297 },
  CITY: { missed: 44, hits: 210, recall: 0.8267716535433071 },
  STATE: { missed: 2, hits: 188, recall: 0.9894736842105263 },

Planeshifter

// MODULES //

const fastXmlParser = require( 'fast-xml-parser' );
const readDir = require( '@stdlib/fs/read-dir' );
const endsWith = require( '@stdlib/string/ends-with' );
const isUppercase = require( '@stdlib/assert/is-uppercase' );
const contains = require( '@stdlib/assert/contains' );
const fs = require( 'fs' );
const join = require( 'path' ).join;

Planeshifter

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Planeshifter

var request = require('request');
var $ = require('cheerio');

var url = 'http://games.espn.com/fba/scoreboard?leagueId=21154&scoringPeriodId=161';

request(url, function(err, resp, body){
    console.log( body )
});