Let T1, T2, · · · , Tn be independent and identically distributed random variables with common c.d.f. F(t)...












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Let T1, T2, · · · , Tn be independent and identically distributed random variables with common c.d.f. F(t).

a- Let Mn = max(T1, T2, · · · , Tn). Find the c.d.f. of Mn in terms of F. (Hint: Note that P(Mn ≤
t) = P(T1 ≤ t, T2 ≤ t, · · · , Tn ≤ t) and use independence of Ti
’s.)

b- Let Nn = min(T1, T2, · · · , Tn). Find the c.d.f. of Nn in terms of F.

c- Suppose that each Ti has Weibull distribution with parameters α > 0 and β > 0. Find E(Nn).*


I cant figure out how to solve it.



Please suggest me a way or tell me what to do?










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$endgroup$



closed as off-topic by NCh, Alexander Gruber Nov 30 '18 at 3:11


This question appears to be off-topic. The users who voted to close gave this specific reason:


  • "This question is missing context or other details: Please improve the question by providing additional context, which ideally includes your thoughts on the problem and any attempts you have made to solve it. This information helps others identify where you have difficulties and helps them write answers appropriate to your experience level." – NCh, Alexander Gruber

If this question can be reworded to fit the rules in the help center, please edit the question.












  • 1




    $begingroup$
    What have you tried so far? How have you used the hint?
    $endgroup$
    – platty
    Nov 29 '18 at 22:32










  • $begingroup$
    I applied the hint but I cannot relate it with F(t).
    $endgroup$
    – mau
    Nov 29 '18 at 22:51
















0












$begingroup$


Let T1, T2, · · · , Tn be independent and identically distributed random variables with common c.d.f. F(t).

a- Let Mn = max(T1, T2, · · · , Tn). Find the c.d.f. of Mn in terms of F. (Hint: Note that P(Mn ≤
t) = P(T1 ≤ t, T2 ≤ t, · · · , Tn ≤ t) and use independence of Ti
’s.)

b- Let Nn = min(T1, T2, · · · , Tn). Find the c.d.f. of Nn in terms of F.

c- Suppose that each Ti has Weibull distribution with parameters α > 0 and β > 0. Find E(Nn).*


I cant figure out how to solve it.



Please suggest me a way or tell me what to do?










share|cite|improve this question











$endgroup$



closed as off-topic by NCh, Alexander Gruber Nov 30 '18 at 3:11


This question appears to be off-topic. The users who voted to close gave this specific reason:


  • "This question is missing context or other details: Please improve the question by providing additional context, which ideally includes your thoughts on the problem and any attempts you have made to solve it. This information helps others identify where you have difficulties and helps them write answers appropriate to your experience level." – NCh, Alexander Gruber

If this question can be reworded to fit the rules in the help center, please edit the question.












  • 1




    $begingroup$
    What have you tried so far? How have you used the hint?
    $endgroup$
    – platty
    Nov 29 '18 at 22:32










  • $begingroup$
    I applied the hint but I cannot relate it with F(t).
    $endgroup$
    – mau
    Nov 29 '18 at 22:51














0












0








0


0



$begingroup$


Let T1, T2, · · · , Tn be independent and identically distributed random variables with common c.d.f. F(t).

a- Let Mn = max(T1, T2, · · · , Tn). Find the c.d.f. of Mn in terms of F. (Hint: Note that P(Mn ≤
t) = P(T1 ≤ t, T2 ≤ t, · · · , Tn ≤ t) and use independence of Ti
’s.)

b- Let Nn = min(T1, T2, · · · , Tn). Find the c.d.f. of Nn in terms of F.

c- Suppose that each Ti has Weibull distribution with parameters α > 0 and β > 0. Find E(Nn).*


I cant figure out how to solve it.



Please suggest me a way or tell me what to do?










share|cite|improve this question











$endgroup$




Let T1, T2, · · · , Tn be independent and identically distributed random variables with common c.d.f. F(t).

a- Let Mn = max(T1, T2, · · · , Tn). Find the c.d.f. of Mn in terms of F. (Hint: Note that P(Mn ≤
t) = P(T1 ≤ t, T2 ≤ t, · · · , Tn ≤ t) and use independence of Ti
’s.)

b- Let Nn = min(T1, T2, · · · , Tn). Find the c.d.f. of Nn in terms of F.

c- Suppose that each Ti has Weibull distribution with parameters α > 0 and β > 0. Find E(Nn).*


I cant figure out how to solve it.



Please suggest me a way or tell me what to do?







probability probability-distributions






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Nov 29 '18 at 22:36







mau

















asked Nov 29 '18 at 22:30









maumau

33




33




closed as off-topic by NCh, Alexander Gruber Nov 30 '18 at 3:11


This question appears to be off-topic. The users who voted to close gave this specific reason:


  • "This question is missing context or other details: Please improve the question by providing additional context, which ideally includes your thoughts on the problem and any attempts you have made to solve it. This information helps others identify where you have difficulties and helps them write answers appropriate to your experience level." – NCh, Alexander Gruber

If this question can be reworded to fit the rules in the help center, please edit the question.







closed as off-topic by NCh, Alexander Gruber Nov 30 '18 at 3:11


This question appears to be off-topic. The users who voted to close gave this specific reason:


  • "This question is missing context or other details: Please improve the question by providing additional context, which ideally includes your thoughts on the problem and any attempts you have made to solve it. This information helps others identify where you have difficulties and helps them write answers appropriate to your experience level." – NCh, Alexander Gruber

If this question can be reworded to fit the rules in the help center, please edit the question.








  • 1




    $begingroup$
    What have you tried so far? How have you used the hint?
    $endgroup$
    – platty
    Nov 29 '18 at 22:32










  • $begingroup$
    I applied the hint but I cannot relate it with F(t).
    $endgroup$
    – mau
    Nov 29 '18 at 22:51














  • 1




    $begingroup$
    What have you tried so far? How have you used the hint?
    $endgroup$
    – platty
    Nov 29 '18 at 22:32










  • $begingroup$
    I applied the hint but I cannot relate it with F(t).
    $endgroup$
    – mau
    Nov 29 '18 at 22:51








1




1




$begingroup$
What have you tried so far? How have you used the hint?
$endgroup$
– platty
Nov 29 '18 at 22:32




$begingroup$
What have you tried so far? How have you used the hint?
$endgroup$
– platty
Nov 29 '18 at 22:32












$begingroup$
I applied the hint but I cannot relate it with F(t).
$endgroup$
– mau
Nov 29 '18 at 22:51




$begingroup$
I applied the hint but I cannot relate it with F(t).
$endgroup$
– mau
Nov 29 '18 at 22:51










1 Answer
1






active

oldest

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$begingroup$

Here are a few hints:



1) If $X$ and $Y$ are independent random variables, with CDF $F_{X}(x)$ and $F_{Y}(y)$, respectively, then $P(Xleq x, Y leq y)=P(Xleq xcap Y leq y)=P(Xleq x) P(Y leq y)=F_{X}(x) F_{Y}(y)$.



2) If $X_{1}$ and $X_{2}$ are identically distributed, then $F_{X_{1}}(x)=F_{X_{2}}(x)equiv F_{X}(x)$.



3) Taking the random variable $M_{n}$, as defined above, the event $lbrace M_{n} leq t rbrace$ is equivalent to the event $lbrace T_{1}leq t cap T_{2} leq t,...,cap T_{n}leq t rbrace$.



4) Taking the random variable $N_{n}$, as defined above, the event $lbrace N_{n} > t rbrace$ is equivalent to the event $lbrace T_{1}>t cap T_{2} >t,...,cap T_{n}>t rbrace$.






share|cite|improve this answer









$endgroup$




















    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0












    $begingroup$

    Here are a few hints:



    1) If $X$ and $Y$ are independent random variables, with CDF $F_{X}(x)$ and $F_{Y}(y)$, respectively, then $P(Xleq x, Y leq y)=P(Xleq xcap Y leq y)=P(Xleq x) P(Y leq y)=F_{X}(x) F_{Y}(y)$.



    2) If $X_{1}$ and $X_{2}$ are identically distributed, then $F_{X_{1}}(x)=F_{X_{2}}(x)equiv F_{X}(x)$.



    3) Taking the random variable $M_{n}$, as defined above, the event $lbrace M_{n} leq t rbrace$ is equivalent to the event $lbrace T_{1}leq t cap T_{2} leq t,...,cap T_{n}leq t rbrace$.



    4) Taking the random variable $N_{n}$, as defined above, the event $lbrace N_{n} > t rbrace$ is equivalent to the event $lbrace T_{1}>t cap T_{2} >t,...,cap T_{n}>t rbrace$.






    share|cite|improve this answer









    $endgroup$


















      0












      $begingroup$

      Here are a few hints:



      1) If $X$ and $Y$ are independent random variables, with CDF $F_{X}(x)$ and $F_{Y}(y)$, respectively, then $P(Xleq x, Y leq y)=P(Xleq xcap Y leq y)=P(Xleq x) P(Y leq y)=F_{X}(x) F_{Y}(y)$.



      2) If $X_{1}$ and $X_{2}$ are identically distributed, then $F_{X_{1}}(x)=F_{X_{2}}(x)equiv F_{X}(x)$.



      3) Taking the random variable $M_{n}$, as defined above, the event $lbrace M_{n} leq t rbrace$ is equivalent to the event $lbrace T_{1}leq t cap T_{2} leq t,...,cap T_{n}leq t rbrace$.



      4) Taking the random variable $N_{n}$, as defined above, the event $lbrace N_{n} > t rbrace$ is equivalent to the event $lbrace T_{1}>t cap T_{2} >t,...,cap T_{n}>t rbrace$.






      share|cite|improve this answer









      $endgroup$
















        0












        0








        0





        $begingroup$

        Here are a few hints:



        1) If $X$ and $Y$ are independent random variables, with CDF $F_{X}(x)$ and $F_{Y}(y)$, respectively, then $P(Xleq x, Y leq y)=P(Xleq xcap Y leq y)=P(Xleq x) P(Y leq y)=F_{X}(x) F_{Y}(y)$.



        2) If $X_{1}$ and $X_{2}$ are identically distributed, then $F_{X_{1}}(x)=F_{X_{2}}(x)equiv F_{X}(x)$.



        3) Taking the random variable $M_{n}$, as defined above, the event $lbrace M_{n} leq t rbrace$ is equivalent to the event $lbrace T_{1}leq t cap T_{2} leq t,...,cap T_{n}leq t rbrace$.



        4) Taking the random variable $N_{n}$, as defined above, the event $lbrace N_{n} > t rbrace$ is equivalent to the event $lbrace T_{1}>t cap T_{2} >t,...,cap T_{n}>t rbrace$.






        share|cite|improve this answer









        $endgroup$



        Here are a few hints:



        1) If $X$ and $Y$ are independent random variables, with CDF $F_{X}(x)$ and $F_{Y}(y)$, respectively, then $P(Xleq x, Y leq y)=P(Xleq xcap Y leq y)=P(Xleq x) P(Y leq y)=F_{X}(x) F_{Y}(y)$.



        2) If $X_{1}$ and $X_{2}$ are identically distributed, then $F_{X_{1}}(x)=F_{X_{2}}(x)equiv F_{X}(x)$.



        3) Taking the random variable $M_{n}$, as defined above, the event $lbrace M_{n} leq t rbrace$ is equivalent to the event $lbrace T_{1}leq t cap T_{2} leq t,...,cap T_{n}leq t rbrace$.



        4) Taking the random variable $N_{n}$, as defined above, the event $lbrace N_{n} > t rbrace$ is equivalent to the event $lbrace T_{1}>t cap T_{2} >t,...,cap T_{n}>t rbrace$.







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Nov 30 '18 at 2:19









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