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The ministry of Health and Long-Term Care in Ontario,

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition | ISBN: 9780495118732 | Authors: Roxy Peck, Chris Olsen, Jay L. Devore ISBN: 9780495118732 197

Solution for problem 4.6 Chapter Chapter 4

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition

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Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition | ISBN: 9780495118732 | Authors: Roxy Peck, Chris Olsen, Jay L. Devore

Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW) | 3rd Edition

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Problem 4.6

The ministry of Health and Long-Term Care in Ontario, Canada, publishes information on its web site (www.health.gov.on.ca) on the time that patients must wait for various medical procedures. For two cardiac procedures completed in fall of 2005 the following information was provided: Number 90% of Com- Median Mean Completed Wait Wait pleted Proce- Time Time Within dures (days) (days) (days) Angioplasty 847 14 18 39 Bypass surgery 539 13 19 42 a. The median wait time for angioplasty is greater than the median wait time for bypass surgery but the mean wait time is shorter for angioplasty than for bypass surgery. What does this suggest about the distribution of wait times for these two procedures? b. Is it possible that another medical procedure might have a median wait time that is greater than the time reported for 90% completed within? Explain.

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Lecture 6: Random Variables 8.1 Random Variables -­ Definition: A random variable assigns a number to each outcome of a random circumstance, or, equivalently, a random variable assigns a number to each unit in a population. -­ Two broad classes of random variables: discrete random variables and continuous random variables. -­ Definitions: A discrete random variable can take one of a countable list of distinct values. Example: Number of years of studies. -­ A continuous random variable can take any value in an interval or collection of intervals. Example: Weight of a group of people Distribution of Random Variable

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Chapter Chapter 4, Problem 4.6 is Solved
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Textbook: Introduction to Statistics and Data Analysis (with CengageNOW Printed Access Card) (Available Titles CengageNOW)
Edition: 3
Author: Roxy Peck, Chris Olsen, Jay L. Devore
ISBN: 9780495118732

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The ministry of Health and Long-Term Care in Ontario,