Researchers at the University of Boston's Children's Hospital and Harvard Medical School analyzed records of breast cancer screening and diagnostic evaluations.† Discussing the downsides of the screening process, the article states that the rate of false-positives is higher than previously thought, and that false-positives lead to unnecessary medical follow-up that can be costly. Suppose that screening is used to decide between a null hypothesis of H0: no cancer is present and an alternative hypothesis of Ha: cancer is present. (Although these are not hypotheses about a population characteristic, this exercise illustrates the definitions of Type I and Type II errors.) Would a false-positive (thinking that cancer is present when in fact it is not) be a Type I error or a Type II error? a. Type I error b. Type II error b. Describe a Type I error in the context of this problem, and discuss the possible consequences of making a Type I error. a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary. b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary. c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary. d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary. c. Describe a Type II error in the context of this problem, and discuss the possible consequences of making a Type II error. a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary. b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary. c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary. d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary.

Researchers at the University of Boston's Children's Hospital and Harvard Medical School analyzed records of breast cancer screening and diagnostic evaluations.† Discussing the downsides of the screening process, the article states that the rate of false-positives is higher than previously thought, and that false-positives lead to unnecessary medical follow-up that can be costly. Suppose that screening is used to decide between a null hypothesis of H0: no cancer is present and an alternative hypothesis of Ha: cancer is present. (Although these are not hypotheses about a population characteristic, this exercise illustrates the definitions of Type I and Type II errors.) Would a false-positive (thinking that cancer is present when in fact it is not) be a Type I error or a Type II error? a. Type I error b. Type II error b. Describe a Type I error in the context of this problem, and discuss the possible consequences of making a Type I error. a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary. b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary. c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary. d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary. c. Describe a Type II error in the context of this problem, and discuss the possible consequences of making a Type II error. a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary. b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary. c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary. d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary.

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Description: Researchers at the University of Boston's Children's Hospital and Harvard Medical School analyzed records of breast cancer screening and diagnostic evaluations.† Discussing the downsides of the screening process, the article states that the rate of f

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Suppose that screening is used to decide between a null hypothesis of

H₀: no cancer is present

and an alternative hypothesis of

H_a: cancer is present.

(Although these are not hypotheses about a population characteristic, this exercise illustrates the definitions of Type I and Type II errors.)

Would a false-positive (thinking that cancer is present when in fact it is not) be a Type I error or a Type II error?

a. Type I error

b. Type II error

Describe a Type I error in the context of this problem, and discuss the possible consequences of making a Type I error.

a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary.

b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary.

c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary.

d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary.

Describe a Type II error in the context of this problem, and discuss the possible consequences of making a Type II error.

a. Coming to the conclusion that cancer is present when, in fact, it is not. Treatment may be started when, in fact, it is not necessary.

b. Coming to the conclusion that cancer is present when, in fact, it is not. No treatment will be prescribed when, in fact, treatment is necessary.

c. Coming to the conclusion that no cancer is present when, in fact, it is present. No treatment will be prescribed when, in fact, treatment is necessary.

d. Coming to the conclusion that no cancer is present when, in fact, it is present. Treatment may be started when, in fact, it is not necessary.

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