Conditional probability problem
$begingroup$
An Internet search engine looks for a keyword in 9 databases, searching them in random order. Only 5 of these databases contain the given keyword. What is the probability that it will be found in at least 2 of the first 4 searched databases?
What I tried is: Let X: the event that the keyword is to be found in at least 2 databases, and Y: the event that we search the first 4 databases,
then we need to find a conditional probability
$P(Xgeq 2 | Y)=P(X= 2,3,text{ or }4 | Y)=frac{P({Xgeq 2} cap Y)}{P(Y)}$
but then I don't know how to continue?
Any help...
probability
$endgroup$
add a comment |
$begingroup$
An Internet search engine looks for a keyword in 9 databases, searching them in random order. Only 5 of these databases contain the given keyword. What is the probability that it will be found in at least 2 of the first 4 searched databases?
What I tried is: Let X: the event that the keyword is to be found in at least 2 databases, and Y: the event that we search the first 4 databases,
then we need to find a conditional probability
$P(Xgeq 2 | Y)=P(X= 2,3,text{ or }4 | Y)=frac{P({Xgeq 2} cap Y)}{P(Y)}$
but then I don't know how to continue?
Any help...
probability
$endgroup$
add a comment |
$begingroup$
An Internet search engine looks for a keyword in 9 databases, searching them in random order. Only 5 of these databases contain the given keyword. What is the probability that it will be found in at least 2 of the first 4 searched databases?
What I tried is: Let X: the event that the keyword is to be found in at least 2 databases, and Y: the event that we search the first 4 databases,
then we need to find a conditional probability
$P(Xgeq 2 | Y)=P(X= 2,3,text{ or }4 | Y)=frac{P({Xgeq 2} cap Y)}{P(Y)}$
but then I don't know how to continue?
Any help...
probability
$endgroup$
An Internet search engine looks for a keyword in 9 databases, searching them in random order. Only 5 of these databases contain the given keyword. What is the probability that it will be found in at least 2 of the first 4 searched databases?
What I tried is: Let X: the event that the keyword is to be found in at least 2 databases, and Y: the event that we search the first 4 databases,
then we need to find a conditional probability
$P(Xgeq 2 | Y)=P(X= 2,3,text{ or }4 | Y)=frac{P({Xgeq 2} cap Y)}{P(Y)}$
but then I don't know how to continue?
Any help...
probability
probability
edited Sep 11 '11 at 0:03
Michael Hardy
1
1
asked Sep 10 '11 at 16:38
KellyKelly
363
363
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
You are going to have to work out the probabilities of getting the keyword exactly $n$ times, and either add up the probabilities for $n=2$, $3$ or $4$, or subtract from $1$ the probabilities for $n=1$ or $0$.
If $N$ is the number of dictionaries where the keyword is found then $$Pr(N=n) = frac{{5 choose n}{4 choose 4-n}}{9 choose 4}$$ since you have to choose $n$ dictionaries from $5$ with the keyword and $4-n$ from $4$ without, choosing $4$ from $9$ overall.
So for $n=0,1,2,3,4$ this gives probabilities $frac{1}{126},frac{20}{126},frac{60}{126},frac{40}{126},frac{5}{126}$.
Add up the last three (and change to lowest terms) and you have your solution.
$endgroup$
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
|
show 1 more comment
$begingroup$
Added: Henry's and my answers, while the approaches are different, actually give the same result! To see why, let's do the general case with $N$ databases, $M$ of which contain the keyword, and us choosing $K$ databases. Let $X$ be the number of the $K$ databases chosen that contain the keyword. For $P(X = x)$, Henry's and my logic give the following answers.
$$text{ Henry: } P(X = x) = frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}}; text{ me: } P(X = x) = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
But
$$frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}} = frac{M!}{x! (M-x)!} frac{(N-M)!}{(K-x)! (N-M-K+x)!} frac{K! (N-K)!}{N!}$$
$$= frac{K!}{x! (K-x)!} frac{(N-K)!}{(M-x)! (N-K-M+x)!} frac{M! (N-M)!}{N!} = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
Thus the two answers give the same result.
(Original answer.)
I would approach it differently. Let $X$ be the number of the first four databases in which the keyword is found. You want $P(X geq 2)$.
$$P(X = 2) = frac{binom{4}{2} binom{5}{3}}{binom{9}{5}}$$ because there are $binom{4}{2}$ ways that 2 of the first 4 databases can contain the keyword, $binom{5}{3}$ ways that 3 of the last 5 databases can contain the keyword, and $binom{9}{5}$ ways that 5 of the 9 total databases to contain the keyword.
I'll let you calculate $P(X = 3)$ and $P(X = 4)$.
(FYI, $X$ has what's called a hypergeometric distribution.)
$endgroup$
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
add a comment |
$begingroup$
Let $t=9$ be total number of databases, of which $n=4$ have no and $k=5$ have the keyword.
Let $c=4$ databases are chosen and $s$ databases have the keyword.
The question is asking to find $sge 2$, i.e. $s=color{red}2,color{green}3,color{blue}4$.
There are ${tchoose c}={9choose 4}$ ways to choose $c$ databases from total $t$ databases.
Case 1: There are ${kchoose 2}={5choose color{red}2}$ ways to choose from $k$ and ${nchoose 2}={4choose 2}$ ways from $n$, hence: ${5choose 2}{4choose 2}$.
Case 2: There are ${kchoose 3}={5choose color{green}3}$ ways to choose from $k$ and ${nchoose 1}={4choose 1}$ ways from $n$, hence: ${5choose 3}{4choose 1}$.
Case 3: There are ${kchoose 4}={5choose color{blue}4}$ ways to choose from $k$ and ${nchoose 0}={4choose 0}$ ways from $n$, hence: ${5choose 4}{4choose 0}$.
Hence, the required probability is:
$$P(sge 2)=P(s=2)+P(s=3)+P(s=4)=\
frac{{5choose 2}{4choose 2}}{9choose 4}+frac{{5choose 3}{4choose 1}}{9choose 4}+frac{{5choose 4}{4choose 0}}{9choose 4}=\
frac{60+40+5}{126}=frac{35}{42}approx 0.83.$$
Note that you can also use the complement, i.e.:
$$P(sge 2)=1-P(s=0)-P(s=1).$$
Thus, in general, the formula is:
$$P(sge r)=sum_{i=r}^c P(s=i)=sum_{i=r}^c frac{{kchoose i}{nchoose c-i}}{{tchoose c}}.$$
Keys: $t$-total, $n$-no keyword, $k$-keyword, $c$-chosen, $s$-success, $r$-minimum required success.
$endgroup$
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
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: "69"
};
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: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
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
});
}
});
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%2fmath.stackexchange.com%2fquestions%2f63356%2fconditional-probability-problem%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
You are going to have to work out the probabilities of getting the keyword exactly $n$ times, and either add up the probabilities for $n=2$, $3$ or $4$, or subtract from $1$ the probabilities for $n=1$ or $0$.
If $N$ is the number of dictionaries where the keyword is found then $$Pr(N=n) = frac{{5 choose n}{4 choose 4-n}}{9 choose 4}$$ since you have to choose $n$ dictionaries from $5$ with the keyword and $4-n$ from $4$ without, choosing $4$ from $9$ overall.
So for $n=0,1,2,3,4$ this gives probabilities $frac{1}{126},frac{20}{126},frac{60}{126},frac{40}{126},frac{5}{126}$.
Add up the last three (and change to lowest terms) and you have your solution.
$endgroup$
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
|
show 1 more comment
$begingroup$
You are going to have to work out the probabilities of getting the keyword exactly $n$ times, and either add up the probabilities for $n=2$, $3$ or $4$, or subtract from $1$ the probabilities for $n=1$ or $0$.
If $N$ is the number of dictionaries where the keyword is found then $$Pr(N=n) = frac{{5 choose n}{4 choose 4-n}}{9 choose 4}$$ since you have to choose $n$ dictionaries from $5$ with the keyword and $4-n$ from $4$ without, choosing $4$ from $9$ overall.
So for $n=0,1,2,3,4$ this gives probabilities $frac{1}{126},frac{20}{126},frac{60}{126},frac{40}{126},frac{5}{126}$.
Add up the last three (and change to lowest terms) and you have your solution.
$endgroup$
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
|
show 1 more comment
$begingroup$
You are going to have to work out the probabilities of getting the keyword exactly $n$ times, and either add up the probabilities for $n=2$, $3$ or $4$, or subtract from $1$ the probabilities for $n=1$ or $0$.
If $N$ is the number of dictionaries where the keyword is found then $$Pr(N=n) = frac{{5 choose n}{4 choose 4-n}}{9 choose 4}$$ since you have to choose $n$ dictionaries from $5$ with the keyword and $4-n$ from $4$ without, choosing $4$ from $9$ overall.
So for $n=0,1,2,3,4$ this gives probabilities $frac{1}{126},frac{20}{126},frac{60}{126},frac{40}{126},frac{5}{126}$.
Add up the last three (and change to lowest terms) and you have your solution.
$endgroup$
You are going to have to work out the probabilities of getting the keyword exactly $n$ times, and either add up the probabilities for $n=2$, $3$ or $4$, or subtract from $1$ the probabilities for $n=1$ or $0$.
If $N$ is the number of dictionaries where the keyword is found then $$Pr(N=n) = frac{{5 choose n}{4 choose 4-n}}{9 choose 4}$$ since you have to choose $n$ dictionaries from $5$ with the keyword and $4-n$ from $4$ without, choosing $4$ from $9$ overall.
So for $n=0,1,2,3,4$ this gives probabilities $frac{1}{126},frac{20}{126},frac{60}{126},frac{40}{126},frac{5}{126}$.
Add up the last three (and change to lowest terms) and you have your solution.
answered Sep 10 '11 at 17:48
HenryHenry
100k481168
100k481168
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
|
show 1 more comment
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
@Mike: I don't know: the value is the same but the words are not. You have ${5 choose 3}$ where I have ${5 choose 2}$, and you say "ways that 3 of the last 5 databases can contain the keyword" while I say "you have to choose 2 dictionaries from 5 with the keyword". Similarly you have ${9 choose 5}$ where I have ${9 choose 4}$, and you say "ways that 5 of the 9 total databases to contain the keyword" while I say "choosing 4 from 9 overall".
$endgroup$
– Henry
Sep 10 '11 at 21:23
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
Suppose there were only 2 databases (rather than 5) that contain the keyword. If I'm following your logic correctly, your answer to that modified problem would be $P(X = 2) = binom{2}{2} binom{7}{2}/binom{9}{4}$ (2 from 2 with keyword, 2 from 7 without keyword, and 4 from 9 overall). The answer, though, is $binom{4}{2}/binom{9}{2}$ (the number of ways to distribute two keywords among a set of 4 divided by the number of ways to distribute two keywords among a set of 9). So I'm not sure that your logic works in general. (Or am I missing something?)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:48
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
So I guess it's not the same as my solution after all. (Deleting earlier comment to that effect.)
$endgroup$
– Mike Spivey
Sep 10 '11 at 21:53
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
In general, if there are $d$ dictionaries and $k$ of them have keywords, and you choose $m$ of them then $Pr(N=n) = dfrac{{k choose n}{d-k choose m-n}}{d choose n}$.
$endgroup$
– Henry
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
$begingroup$
Huh. Even in the example I sort of picked at random, our logic still gives the same numerical answer! Perhaps our answers are equivalent after all, even when they don't look like it. Unfortunately, I don't have time right now to pursue this any further. +1 from me.
$endgroup$
– Mike Spivey
Sep 10 '11 at 22:09
|
show 1 more comment
$begingroup$
Added: Henry's and my answers, while the approaches are different, actually give the same result! To see why, let's do the general case with $N$ databases, $M$ of which contain the keyword, and us choosing $K$ databases. Let $X$ be the number of the $K$ databases chosen that contain the keyword. For $P(X = x)$, Henry's and my logic give the following answers.
$$text{ Henry: } P(X = x) = frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}}; text{ me: } P(X = x) = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
But
$$frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}} = frac{M!}{x! (M-x)!} frac{(N-M)!}{(K-x)! (N-M-K+x)!} frac{K! (N-K)!}{N!}$$
$$= frac{K!}{x! (K-x)!} frac{(N-K)!}{(M-x)! (N-K-M+x)!} frac{M! (N-M)!}{N!} = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
Thus the two answers give the same result.
(Original answer.)
I would approach it differently. Let $X$ be the number of the first four databases in which the keyword is found. You want $P(X geq 2)$.
$$P(X = 2) = frac{binom{4}{2} binom{5}{3}}{binom{9}{5}}$$ because there are $binom{4}{2}$ ways that 2 of the first 4 databases can contain the keyword, $binom{5}{3}$ ways that 3 of the last 5 databases can contain the keyword, and $binom{9}{5}$ ways that 5 of the 9 total databases to contain the keyword.
I'll let you calculate $P(X = 3)$ and $P(X = 4)$.
(FYI, $X$ has what's called a hypergeometric distribution.)
$endgroup$
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
add a comment |
$begingroup$
Added: Henry's and my answers, while the approaches are different, actually give the same result! To see why, let's do the general case with $N$ databases, $M$ of which contain the keyword, and us choosing $K$ databases. Let $X$ be the number of the $K$ databases chosen that contain the keyword. For $P(X = x)$, Henry's and my logic give the following answers.
$$text{ Henry: } P(X = x) = frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}}; text{ me: } P(X = x) = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
But
$$frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}} = frac{M!}{x! (M-x)!} frac{(N-M)!}{(K-x)! (N-M-K+x)!} frac{K! (N-K)!}{N!}$$
$$= frac{K!}{x! (K-x)!} frac{(N-K)!}{(M-x)! (N-K-M+x)!} frac{M! (N-M)!}{N!} = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
Thus the two answers give the same result.
(Original answer.)
I would approach it differently. Let $X$ be the number of the first four databases in which the keyword is found. You want $P(X geq 2)$.
$$P(X = 2) = frac{binom{4}{2} binom{5}{3}}{binom{9}{5}}$$ because there are $binom{4}{2}$ ways that 2 of the first 4 databases can contain the keyword, $binom{5}{3}$ ways that 3 of the last 5 databases can contain the keyword, and $binom{9}{5}$ ways that 5 of the 9 total databases to contain the keyword.
I'll let you calculate $P(X = 3)$ and $P(X = 4)$.
(FYI, $X$ has what's called a hypergeometric distribution.)
$endgroup$
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
add a comment |
$begingroup$
Added: Henry's and my answers, while the approaches are different, actually give the same result! To see why, let's do the general case with $N$ databases, $M$ of which contain the keyword, and us choosing $K$ databases. Let $X$ be the number of the $K$ databases chosen that contain the keyword. For $P(X = x)$, Henry's and my logic give the following answers.
$$text{ Henry: } P(X = x) = frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}}; text{ me: } P(X = x) = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
But
$$frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}} = frac{M!}{x! (M-x)!} frac{(N-M)!}{(K-x)! (N-M-K+x)!} frac{K! (N-K)!}{N!}$$
$$= frac{K!}{x! (K-x)!} frac{(N-K)!}{(M-x)! (N-K-M+x)!} frac{M! (N-M)!}{N!} = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
Thus the two answers give the same result.
(Original answer.)
I would approach it differently. Let $X$ be the number of the first four databases in which the keyword is found. You want $P(X geq 2)$.
$$P(X = 2) = frac{binom{4}{2} binom{5}{3}}{binom{9}{5}}$$ because there are $binom{4}{2}$ ways that 2 of the first 4 databases can contain the keyword, $binom{5}{3}$ ways that 3 of the last 5 databases can contain the keyword, and $binom{9}{5}$ ways that 5 of the 9 total databases to contain the keyword.
I'll let you calculate $P(X = 3)$ and $P(X = 4)$.
(FYI, $X$ has what's called a hypergeometric distribution.)
$endgroup$
Added: Henry's and my answers, while the approaches are different, actually give the same result! To see why, let's do the general case with $N$ databases, $M$ of which contain the keyword, and us choosing $K$ databases. Let $X$ be the number of the $K$ databases chosen that contain the keyword. For $P(X = x)$, Henry's and my logic give the following answers.
$$text{ Henry: } P(X = x) = frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}}; text{ me: } P(X = x) = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
But
$$frac{binom{M}{x}binom{N-M}{K-x}}{binom{N}{K}} = frac{M!}{x! (M-x)!} frac{(N-M)!}{(K-x)! (N-M-K+x)!} frac{K! (N-K)!}{N!}$$
$$= frac{K!}{x! (K-x)!} frac{(N-K)!}{(M-x)! (N-K-M+x)!} frac{M! (N-M)!}{N!} = frac{binom{K}{x} binom{N-K}{M-x}}{binom{N}{M}}.$$
Thus the two answers give the same result.
(Original answer.)
I would approach it differently. Let $X$ be the number of the first four databases in which the keyword is found. You want $P(X geq 2)$.
$$P(X = 2) = frac{binom{4}{2} binom{5}{3}}{binom{9}{5}}$$ because there are $binom{4}{2}$ ways that 2 of the first 4 databases can contain the keyword, $binom{5}{3}$ ways that 3 of the last 5 databases can contain the keyword, and $binom{9}{5}$ ways that 5 of the 9 total databases to contain the keyword.
I'll let you calculate $P(X = 3)$ and $P(X = 4)$.
(FYI, $X$ has what's called a hypergeometric distribution.)
edited Sep 10 '11 at 23:37
answered Sep 10 '11 at 16:53
Mike SpiveyMike Spivey
42.6k8143233
42.6k8143233
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
add a comment |
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
So, in general: $P(X=k)=frac{binom{4}{k} binom{5}{5-k}}{binom{9}{5}} $
$endgroup$
– Kelly
Sep 10 '11 at 16:56
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
@Jess: Yep. That's the form of the probability mass function for a hypergeometric distribution.
$endgroup$
– Mike Spivey
Sep 10 '11 at 17:05
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
I feel that there is something wrong above! Are we choosing 4 items and not 5?!
$endgroup$
– Kelly
Sep 10 '11 at 17:06
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
$begingroup$
@Jess: I was looking at the problem from the point of view of placing 5 keywords into 9 databases. So we are choosing 5 items (databases) in which to place the keywords.
$endgroup$
– Mike Spivey
Sep 10 '11 at 20:31
add a comment |
$begingroup$
Let $t=9$ be total number of databases, of which $n=4$ have no and $k=5$ have the keyword.
Let $c=4$ databases are chosen and $s$ databases have the keyword.
The question is asking to find $sge 2$, i.e. $s=color{red}2,color{green}3,color{blue}4$.
There are ${tchoose c}={9choose 4}$ ways to choose $c$ databases from total $t$ databases.
Case 1: There are ${kchoose 2}={5choose color{red}2}$ ways to choose from $k$ and ${nchoose 2}={4choose 2}$ ways from $n$, hence: ${5choose 2}{4choose 2}$.
Case 2: There are ${kchoose 3}={5choose color{green}3}$ ways to choose from $k$ and ${nchoose 1}={4choose 1}$ ways from $n$, hence: ${5choose 3}{4choose 1}$.
Case 3: There are ${kchoose 4}={5choose color{blue}4}$ ways to choose from $k$ and ${nchoose 0}={4choose 0}$ ways from $n$, hence: ${5choose 4}{4choose 0}$.
Hence, the required probability is:
$$P(sge 2)=P(s=2)+P(s=3)+P(s=4)=\
frac{{5choose 2}{4choose 2}}{9choose 4}+frac{{5choose 3}{4choose 1}}{9choose 4}+frac{{5choose 4}{4choose 0}}{9choose 4}=\
frac{60+40+5}{126}=frac{35}{42}approx 0.83.$$
Note that you can also use the complement, i.e.:
$$P(sge 2)=1-P(s=0)-P(s=1).$$
Thus, in general, the formula is:
$$P(sge r)=sum_{i=r}^c P(s=i)=sum_{i=r}^c frac{{kchoose i}{nchoose c-i}}{{tchoose c}}.$$
Keys: $t$-total, $n$-no keyword, $k$-keyword, $c$-chosen, $s$-success, $r$-minimum required success.
$endgroup$
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
add a comment |
$begingroup$
Let $t=9$ be total number of databases, of which $n=4$ have no and $k=5$ have the keyword.
Let $c=4$ databases are chosen and $s$ databases have the keyword.
The question is asking to find $sge 2$, i.e. $s=color{red}2,color{green}3,color{blue}4$.
There are ${tchoose c}={9choose 4}$ ways to choose $c$ databases from total $t$ databases.
Case 1: There are ${kchoose 2}={5choose color{red}2}$ ways to choose from $k$ and ${nchoose 2}={4choose 2}$ ways from $n$, hence: ${5choose 2}{4choose 2}$.
Case 2: There are ${kchoose 3}={5choose color{green}3}$ ways to choose from $k$ and ${nchoose 1}={4choose 1}$ ways from $n$, hence: ${5choose 3}{4choose 1}$.
Case 3: There are ${kchoose 4}={5choose color{blue}4}$ ways to choose from $k$ and ${nchoose 0}={4choose 0}$ ways from $n$, hence: ${5choose 4}{4choose 0}$.
Hence, the required probability is:
$$P(sge 2)=P(s=2)+P(s=3)+P(s=4)=\
frac{{5choose 2}{4choose 2}}{9choose 4}+frac{{5choose 3}{4choose 1}}{9choose 4}+frac{{5choose 4}{4choose 0}}{9choose 4}=\
frac{60+40+5}{126}=frac{35}{42}approx 0.83.$$
Note that you can also use the complement, i.e.:
$$P(sge 2)=1-P(s=0)-P(s=1).$$
Thus, in general, the formula is:
$$P(sge r)=sum_{i=r}^c P(s=i)=sum_{i=r}^c frac{{kchoose i}{nchoose c-i}}{{tchoose c}}.$$
Keys: $t$-total, $n$-no keyword, $k$-keyword, $c$-chosen, $s$-success, $r$-minimum required success.
$endgroup$
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
add a comment |
$begingroup$
Let $t=9$ be total number of databases, of which $n=4$ have no and $k=5$ have the keyword.
Let $c=4$ databases are chosen and $s$ databases have the keyword.
The question is asking to find $sge 2$, i.e. $s=color{red}2,color{green}3,color{blue}4$.
There are ${tchoose c}={9choose 4}$ ways to choose $c$ databases from total $t$ databases.
Case 1: There are ${kchoose 2}={5choose color{red}2}$ ways to choose from $k$ and ${nchoose 2}={4choose 2}$ ways from $n$, hence: ${5choose 2}{4choose 2}$.
Case 2: There are ${kchoose 3}={5choose color{green}3}$ ways to choose from $k$ and ${nchoose 1}={4choose 1}$ ways from $n$, hence: ${5choose 3}{4choose 1}$.
Case 3: There are ${kchoose 4}={5choose color{blue}4}$ ways to choose from $k$ and ${nchoose 0}={4choose 0}$ ways from $n$, hence: ${5choose 4}{4choose 0}$.
Hence, the required probability is:
$$P(sge 2)=P(s=2)+P(s=3)+P(s=4)=\
frac{{5choose 2}{4choose 2}}{9choose 4}+frac{{5choose 3}{4choose 1}}{9choose 4}+frac{{5choose 4}{4choose 0}}{9choose 4}=\
frac{60+40+5}{126}=frac{35}{42}approx 0.83.$$
Note that you can also use the complement, i.e.:
$$P(sge 2)=1-P(s=0)-P(s=1).$$
Thus, in general, the formula is:
$$P(sge r)=sum_{i=r}^c P(s=i)=sum_{i=r}^c frac{{kchoose i}{nchoose c-i}}{{tchoose c}}.$$
Keys: $t$-total, $n$-no keyword, $k$-keyword, $c$-chosen, $s$-success, $r$-minimum required success.
$endgroup$
Let $t=9$ be total number of databases, of which $n=4$ have no and $k=5$ have the keyword.
Let $c=4$ databases are chosen and $s$ databases have the keyword.
The question is asking to find $sge 2$, i.e. $s=color{red}2,color{green}3,color{blue}4$.
There are ${tchoose c}={9choose 4}$ ways to choose $c$ databases from total $t$ databases.
Case 1: There are ${kchoose 2}={5choose color{red}2}$ ways to choose from $k$ and ${nchoose 2}={4choose 2}$ ways from $n$, hence: ${5choose 2}{4choose 2}$.
Case 2: There are ${kchoose 3}={5choose color{green}3}$ ways to choose from $k$ and ${nchoose 1}={4choose 1}$ ways from $n$, hence: ${5choose 3}{4choose 1}$.
Case 3: There are ${kchoose 4}={5choose color{blue}4}$ ways to choose from $k$ and ${nchoose 0}={4choose 0}$ ways from $n$, hence: ${5choose 4}{4choose 0}$.
Hence, the required probability is:
$$P(sge 2)=P(s=2)+P(s=3)+P(s=4)=\
frac{{5choose 2}{4choose 2}}{9choose 4}+frac{{5choose 3}{4choose 1}}{9choose 4}+frac{{5choose 4}{4choose 0}}{9choose 4}=\
frac{60+40+5}{126}=frac{35}{42}approx 0.83.$$
Note that you can also use the complement, i.e.:
$$P(sge 2)=1-P(s=0)-P(s=1).$$
Thus, in general, the formula is:
$$P(sge r)=sum_{i=r}^c P(s=i)=sum_{i=r}^c frac{{kchoose i}{nchoose c-i}}{{tchoose c}}.$$
Keys: $t$-total, $n$-no keyword, $k$-keyword, $c$-chosen, $s$-success, $r$-minimum required success.
answered Jan 1 at 11:26
farruhotafarruhota
20.5k2739
20.5k2739
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
add a comment |
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
Useful, after the answers from 7 years ago?
$endgroup$
– Did
Jan 1 at 12:12
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
@Did, I tried to summarize and generalize the other answers.
$endgroup$
– farruhota
Jan 1 at 12:21
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
How did you fall on this question and why did you decide to "reawaken" it?
$endgroup$
– Did
Jan 1 at 12:24
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
@Did, the third answer brought it up, I read the discussions in comments and decided to organize the answers. Oh well, I see the OP has been off since then. So, it looks the problem will hang out unaccepted.
$endgroup$
– farruhota
Jan 1 at 12:29
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
$begingroup$
Thanks. I've read the question and all answers again; seem that I misunderstood the question (4 searched databases here mean each search hit distinguished database); the answer has been deleted.
$endgroup$
– o0omycomputero0o
Jan 1 at 15:03
add a comment |
Thanks for contributing an answer to Mathematics 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%2fmath.stackexchange.com%2fquestions%2f63356%2fconditional-probability-problem%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