Conditional probability problem












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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...










share|cite|improve this question











$endgroup$

















    4












    $begingroup$


    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...










    share|cite|improve this question











    $endgroup$















      4












      4








      4


      1



      $begingroup$


      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...










      share|cite|improve this question











      $endgroup$




      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






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      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Sep 11 '11 at 0:03









      Michael Hardy

      1




      1










      asked Sep 10 '11 at 16:38









      KellyKelly

      363




      363






















          3 Answers
          3






          active

          oldest

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          3












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            @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



















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          $begingroup$

          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.)






          share|cite|improve this answer











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          • $begingroup$
            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



















          0












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            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











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          3 Answers
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          3 Answers
          3






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          active

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          active

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          3












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            @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
















          3












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            @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














          3












          3








          3





          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$



          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.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          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


















          • $begingroup$
            @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











          3












          $begingroup$

          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.)






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            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
















          3












          $begingroup$

          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.)






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            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














          3












          3








          3





          $begingroup$

          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.)






          share|cite|improve this answer











          $endgroup$



          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.)







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          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


















          • $begingroup$
            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











          0












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            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
















          0












          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            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














          0












          0








          0





          $begingroup$

          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.






          share|cite|improve this answer









          $endgroup$



          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.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          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


















          • $begingroup$
            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


















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