Prove $P({Xge t}cup{Yge t})le t^{-2}(1+sqrt{1-r^2})$ where $r$ is the correlation of $X$ and $Y$ centered...












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Let $xi$ and $eta$ be random variables with variances $mathbb{D}xi$ and $mathbb{D}eta$, and correlation coefficient $rho$. Show that $$mathbb{P}({xi - mathbb{E}xi geq varepsilon sqrt{mathbb{D}xi} } cup { eta - mathbb{E}eta geq varepsilon sqrt{mathbb{D}eta}) leq frac{1}{varepsilon^2}(1+sqrt{1-rho^2}).$$




So, if I am right, I see a connection with $$mathbb{E}max{xi^2,eta^2}leq 1 + sqrt{1-rho^2}.$$ But actually don't know how to use it here.










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    0












    $begingroup$



    Let $xi$ and $eta$ be random variables with variances $mathbb{D}xi$ and $mathbb{D}eta$, and correlation coefficient $rho$. Show that $$mathbb{P}({xi - mathbb{E}xi geq varepsilon sqrt{mathbb{D}xi} } cup { eta - mathbb{E}eta geq varepsilon sqrt{mathbb{D}eta}) leq frac{1}{varepsilon^2}(1+sqrt{1-rho^2}).$$




    So, if I am right, I see a connection with $$mathbb{E}max{xi^2,eta^2}leq 1 + sqrt{1-rho^2}.$$ But actually don't know how to use it here.










    share|cite|improve this question











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      0












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      0


      0



      $begingroup$



      Let $xi$ and $eta$ be random variables with variances $mathbb{D}xi$ and $mathbb{D}eta$, and correlation coefficient $rho$. Show that $$mathbb{P}({xi - mathbb{E}xi geq varepsilon sqrt{mathbb{D}xi} } cup { eta - mathbb{E}eta geq varepsilon sqrt{mathbb{D}eta}) leq frac{1}{varepsilon^2}(1+sqrt{1-rho^2}).$$




      So, if I am right, I see a connection with $$mathbb{E}max{xi^2,eta^2}leq 1 + sqrt{1-rho^2}.$$ But actually don't know how to use it here.










      share|cite|improve this question











      $endgroup$





      Let $xi$ and $eta$ be random variables with variances $mathbb{D}xi$ and $mathbb{D}eta$, and correlation coefficient $rho$. Show that $$mathbb{P}({xi - mathbb{E}xi geq varepsilon sqrt{mathbb{D}xi} } cup { eta - mathbb{E}eta geq varepsilon sqrt{mathbb{D}eta}) leq frac{1}{varepsilon^2}(1+sqrt{1-rho^2}).$$




      So, if I am right, I see a connection with $$mathbb{E}max{xi^2,eta^2}leq 1 + sqrt{1-rho^2}.$$ But actually don't know how to use it here.







      probability-theory random-variables correlation






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      edited Dec 18 '18 at 20:14









      Did

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      asked Dec 18 '18 at 19:36









      AtstovasAtstovas

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          1 Answer
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          $begingroup$

          WLOG after renormalizing, both variables have mean zero and dispersions equal to one, so we can write this as
          $$
          defe{varepsilon}
          P(xige ecup etage e)=P(max(xi,eta)gee)le P(max(xi^2,eta^2)ge e^2).
          $$

          Now, use Markov's inequality to relate this to $E[max(xi^2,eta^2)]$.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:51












          • $begingroup$
            No, you only need to deal with $E[max(xi^2,eta^2)]$.
            $endgroup$
            – Mike Earnest
            Dec 18 '18 at 20:52










          • $begingroup$
            Oh, ok. Then I done with it. Thank you for your help
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:54












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          $begingroup$

          WLOG after renormalizing, both variables have mean zero and dispersions equal to one, so we can write this as
          $$
          defe{varepsilon}
          P(xige ecup etage e)=P(max(xi,eta)gee)le P(max(xi^2,eta^2)ge e^2).
          $$

          Now, use Markov's inequality to relate this to $E[max(xi^2,eta^2)]$.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:51












          • $begingroup$
            No, you only need to deal with $E[max(xi^2,eta^2)]$.
            $endgroup$
            – Mike Earnest
            Dec 18 '18 at 20:52










          • $begingroup$
            Oh, ok. Then I done with it. Thank you for your help
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:54
















          1












          $begingroup$

          WLOG after renormalizing, both variables have mean zero and dispersions equal to one, so we can write this as
          $$
          defe{varepsilon}
          P(xige ecup etage e)=P(max(xi,eta)gee)le P(max(xi^2,eta^2)ge e^2).
          $$

          Now, use Markov's inequality to relate this to $E[max(xi^2,eta^2)]$.






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:51












          • $begingroup$
            No, you only need to deal with $E[max(xi^2,eta^2)]$.
            $endgroup$
            – Mike Earnest
            Dec 18 '18 at 20:52










          • $begingroup$
            Oh, ok. Then I done with it. Thank you for your help
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:54














          1












          1








          1





          $begingroup$

          WLOG after renormalizing, both variables have mean zero and dispersions equal to one, so we can write this as
          $$
          defe{varepsilon}
          P(xige ecup etage e)=P(max(xi,eta)gee)le P(max(xi^2,eta^2)ge e^2).
          $$

          Now, use Markov's inequality to relate this to $E[max(xi^2,eta^2)]$.






          share|cite|improve this answer









          $endgroup$



          WLOG after renormalizing, both variables have mean zero and dispersions equal to one, so we can write this as
          $$
          defe{varepsilon}
          P(xige ecup etage e)=P(max(xi,eta)gee)le P(max(xi^2,eta^2)ge e^2).
          $$

          Now, use Markov's inequality to relate this to $E[max(xi^2,eta^2)]$.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Dec 18 '18 at 20:20









          Mike EarnestMike Earnest

          26.1k22151




          26.1k22151












          • $begingroup$
            Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:51












          • $begingroup$
            No, you only need to deal with $E[max(xi^2,eta^2)]$.
            $endgroup$
            – Mike Earnest
            Dec 18 '18 at 20:52










          • $begingroup$
            Oh, ok. Then I done with it. Thank you for your help
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:54


















          • $begingroup$
            Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:51












          • $begingroup$
            No, you only need to deal with $E[max(xi^2,eta^2)]$.
            $endgroup$
            – Mike Earnest
            Dec 18 '18 at 20:52










          • $begingroup$
            Oh, ok. Then I done with it. Thank you for your help
            $endgroup$
            – Atstovas
            Dec 18 '18 at 20:54
















          $begingroup$
          Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
          $endgroup$
          – Atstovas
          Dec 18 '18 at 20:51






          $begingroup$
          Thank you. How to prove right inequality's side I know, but do I need to find $E(max{ (xi,eta) }$? If yes, then I have problems with it... I did everything the same, but don't know how much is $mathbb{E}(sqrt{xi}sqrt{eta})$. Is it equal to $sqrt{rho}$?
          $endgroup$
          – Atstovas
          Dec 18 '18 at 20:51














          $begingroup$
          No, you only need to deal with $E[max(xi^2,eta^2)]$.
          $endgroup$
          – Mike Earnest
          Dec 18 '18 at 20:52




          $begingroup$
          No, you only need to deal with $E[max(xi^2,eta^2)]$.
          $endgroup$
          – Mike Earnest
          Dec 18 '18 at 20:52












          $begingroup$
          Oh, ok. Then I done with it. Thank you for your help
          $endgroup$
          – Atstovas
          Dec 18 '18 at 20:54




          $begingroup$
          Oh, ok. Then I done with it. Thank you for your help
          $endgroup$
          – Atstovas
          Dec 18 '18 at 20:54


















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