Type 1 Error & Type 2 Error's pregnancy test analogy: is it legit?Goldfeld - Quandt test statistic equal...
Infinite past with a beginning?
How to type dʒ symbol (IPA) on Mac?
How does one intimidate enemies without having the capacity for violence?
Example of a relative pronoun
Motorized valve interfering with button?
How old can references or sources in a thesis be?
XeLaTeX and pdfLaTeX ignore hyphenation
"which" command doesn't work / path of Safari?
Why Is Death Allowed In the Matrix?
Find original functions from a composite function
What are these boxed doors outside store fronts in New York?
What is the command to reset a PC without deleting any files
Set-theoretical foundations of Mathematics with only bounded quantifiers
whey we use polarized capacitor?
Validation accuracy vs Testing accuracy
Book about a traveler who helps planets in need
Continuity at a point in terms of closure
How is it possible for user to changed after storage was encrypted? (on OS X, Android)
How to re-create Edward Weson's Pepper No. 30?
Why has Russell's definition of numbers using equivalence classes been finally abandoned? ( If it has actually been abandoned).
How can I fix this gap between bookcases I made?
GPS Rollover on Android Smartphones
What defenses are there against being summoned by the Gate spell?
Why did the Germans forbid the possession of pet pigeons in Rostov-on-Don in 1941?
Type 1 Error & Type 2 Error's pregnancy test analogy: is it legit?
Goldfeld - Quandt test statistic equal to 1Test of two variance ratios being equalChristiano Fitzgerald filtering processWhat is the standard error on quarterly GDP figure?Using the sample mean to test hypothesesIf someone stays at home because they can't find the type of job they want, are they included in unemployment numbers?Multivariate linear regression: how to test for whether the slopes are the same?
$begingroup$
I found this picture in my stats book but I'm now confused to what 'positive' and 'negative' is referring to.
As seen in the table below, Type 1 error is the error that its H0 is actually true but FALSEly claims that it's false. Type 2 error, on the other hand, is the error that its H0 is actually false but FALSEly claims that it's true.
So my question is, how do the pregnancy analogy and whole 'false positive' & 'false negative' thing make sense?
For the first picture to be a type 1 error, H0 should be "The person is NOT pregnant" so that "You're pregnant" statement becomes false.
However, the second picture has the complete opposite H0, where H0 should be "The person is pregnant" so that "You're not pregnant" statement becomes false.
I thought it was really confusing because I thought false POSITIVE and false NEGATIVE corresponded to "You're pregnant"(positive) / "You're NOT pregnant"(negative)
But based on the table below, that doesn't seem to make any sense.
So the question is, is there anything that I'm missing here or is it just that textbook's analogy sucks?
statistics
New contributor
$endgroup$
add a comment |
$begingroup$
I found this picture in my stats book but I'm now confused to what 'positive' and 'negative' is referring to.
As seen in the table below, Type 1 error is the error that its H0 is actually true but FALSEly claims that it's false. Type 2 error, on the other hand, is the error that its H0 is actually false but FALSEly claims that it's true.
So my question is, how do the pregnancy analogy and whole 'false positive' & 'false negative' thing make sense?
For the first picture to be a type 1 error, H0 should be "The person is NOT pregnant" so that "You're pregnant" statement becomes false.
However, the second picture has the complete opposite H0, where H0 should be "The person is pregnant" so that "You're not pregnant" statement becomes false.
I thought it was really confusing because I thought false POSITIVE and false NEGATIVE corresponded to "You're pregnant"(positive) / "You're NOT pregnant"(negative)
But based on the table below, that doesn't seem to make any sense.
So the question is, is there anything that I'm missing here or is it just that textbook's analogy sucks?
statistics
New contributor
$endgroup$
add a comment |
$begingroup$
I found this picture in my stats book but I'm now confused to what 'positive' and 'negative' is referring to.
As seen in the table below, Type 1 error is the error that its H0 is actually true but FALSEly claims that it's false. Type 2 error, on the other hand, is the error that its H0 is actually false but FALSEly claims that it's true.
So my question is, how do the pregnancy analogy and whole 'false positive' & 'false negative' thing make sense?
For the first picture to be a type 1 error, H0 should be "The person is NOT pregnant" so that "You're pregnant" statement becomes false.
However, the second picture has the complete opposite H0, where H0 should be "The person is pregnant" so that "You're not pregnant" statement becomes false.
I thought it was really confusing because I thought false POSITIVE and false NEGATIVE corresponded to "You're pregnant"(positive) / "You're NOT pregnant"(negative)
But based on the table below, that doesn't seem to make any sense.
So the question is, is there anything that I'm missing here or is it just that textbook's analogy sucks?
statistics
New contributor
$endgroup$
I found this picture in my stats book but I'm now confused to what 'positive' and 'negative' is referring to.
As seen in the table below, Type 1 error is the error that its H0 is actually true but FALSEly claims that it's false. Type 2 error, on the other hand, is the error that its H0 is actually false but FALSEly claims that it's true.
So my question is, how do the pregnancy analogy and whole 'false positive' & 'false negative' thing make sense?
For the first picture to be a type 1 error, H0 should be "The person is NOT pregnant" so that "You're pregnant" statement becomes false.
However, the second picture has the complete opposite H0, where H0 should be "The person is pregnant" so that "You're not pregnant" statement becomes false.
I thought it was really confusing because I thought false POSITIVE and false NEGATIVE corresponded to "You're pregnant"(positive) / "You're NOT pregnant"(negative)
But based on the table below, that doesn't seem to make any sense.
So the question is, is there anything that I'm missing here or is it just that textbook's analogy sucks?
statistics
statistics
New contributor
New contributor
New contributor
asked 11 hours ago
user8491363user8491363
132
132
New contributor
New contributor
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
Presumably here
- the null hypothesis is $H_0:$ You are not pregnant
- the alternative hypothesis is $H_1:$ You are pregnant
so being pregnant would be the positive result.
You take a pregnancy test
if the pregnancy test gives a positive result when you are not pregnant then this is a false positive, a Type I error when the null hypothesis $H_0$ is in fact true but has been rejected by the test
if the pregnancy test gives a negative result when you are pregnant then this is a false negative, a Type II error when the null hypothesis $H_0$ is in fact untrue but has not been rejected by the test
So in a statement of being a true/false positive/negative test, the true/false part is about the accuracy of the test while the positive/negative part is about the result of the test rather than being the real situation
$endgroup$
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "591"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
user8491363 is a new contributor. Be nice, and check out our Code of Conduct.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2feconomics.stackexchange.com%2fquestions%2f27677%2ftype-1-error-type-2-errors-pregnancy-test-analogy-is-it-legit%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Presumably here
- the null hypothesis is $H_0:$ You are not pregnant
- the alternative hypothesis is $H_1:$ You are pregnant
so being pregnant would be the positive result.
You take a pregnancy test
if the pregnancy test gives a positive result when you are not pregnant then this is a false positive, a Type I error when the null hypothesis $H_0$ is in fact true but has been rejected by the test
if the pregnancy test gives a negative result when you are pregnant then this is a false negative, a Type II error when the null hypothesis $H_0$ is in fact untrue but has not been rejected by the test
So in a statement of being a true/false positive/negative test, the true/false part is about the accuracy of the test while the positive/negative part is about the result of the test rather than being the real situation
$endgroup$
add a comment |
$begingroup$
Presumably here
- the null hypothesis is $H_0:$ You are not pregnant
- the alternative hypothesis is $H_1:$ You are pregnant
so being pregnant would be the positive result.
You take a pregnancy test
if the pregnancy test gives a positive result when you are not pregnant then this is a false positive, a Type I error when the null hypothesis $H_0$ is in fact true but has been rejected by the test
if the pregnancy test gives a negative result when you are pregnant then this is a false negative, a Type II error when the null hypothesis $H_0$ is in fact untrue but has not been rejected by the test
So in a statement of being a true/false positive/negative test, the true/false part is about the accuracy of the test while the positive/negative part is about the result of the test rather than being the real situation
$endgroup$
add a comment |
$begingroup$
Presumably here
- the null hypothesis is $H_0:$ You are not pregnant
- the alternative hypothesis is $H_1:$ You are pregnant
so being pregnant would be the positive result.
You take a pregnancy test
if the pregnancy test gives a positive result when you are not pregnant then this is a false positive, a Type I error when the null hypothesis $H_0$ is in fact true but has been rejected by the test
if the pregnancy test gives a negative result when you are pregnant then this is a false negative, a Type II error when the null hypothesis $H_0$ is in fact untrue but has not been rejected by the test
So in a statement of being a true/false positive/negative test, the true/false part is about the accuracy of the test while the positive/negative part is about the result of the test rather than being the real situation
$endgroup$
Presumably here
- the null hypothesis is $H_0:$ You are not pregnant
- the alternative hypothesis is $H_1:$ You are pregnant
so being pregnant would be the positive result.
You take a pregnancy test
if the pregnancy test gives a positive result when you are not pregnant then this is a false positive, a Type I error when the null hypothesis $H_0$ is in fact true but has been rejected by the test
if the pregnancy test gives a negative result when you are pregnant then this is a false negative, a Type II error when the null hypothesis $H_0$ is in fact untrue but has not been rejected by the test
So in a statement of being a true/false positive/negative test, the true/false part is about the accuracy of the test while the positive/negative part is about the result of the test rather than being the real situation
answered 10 hours ago
HenryHenry
3,826316
3,826316
add a comment |
add a comment |
user8491363 is a new contributor. Be nice, and check out our Code of Conduct.
user8491363 is a new contributor. Be nice, and check out our Code of Conduct.
user8491363 is a new contributor. Be nice, and check out our Code of Conduct.
user8491363 is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Economics Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2feconomics.stackexchange.com%2fquestions%2f27677%2ftype-1-error-type-2-errors-pregnancy-test-analogy-is-it-legit%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown