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Lower bound on the probability that a random variable is greater than half of its mean


Lower bound for tail probabilityWhy the result of probability density function of a random variable is greater than 1?What conditions are needed for a uniform bound on the deviation of a random variable from its expectation?Analogous of Markov's inequality for the lower boundLower bound for (function of) density of well-behaved random variableHow to find a lower bound of the probability of a Gaussian random variableSingle random variable, multiple probability distributions?Sample Space as the image of a Random Variable?Lower bound for left tail probabilityIs there a way to lower bound the left tail probability of a random variable?













1












$begingroup$


Consider a random variable $X$ that takes values between $-1$ and $1$. What is a non-trivial lower bound on the probability that the outcome of $X$ is greater than half of its mean?




EDIT:



I am looking for a bound that is a function of the mean (and so would cover the case where the mean is positive).



I.e.



$textPr left[ X > mathbbE[X] over 2 right] geq f(mathbbE[X]).$










share|cite|improve this question











$endgroup$
















    1












    $begingroup$


    Consider a random variable $X$ that takes values between $-1$ and $1$. What is a non-trivial lower bound on the probability that the outcome of $X$ is greater than half of its mean?




    EDIT:



    I am looking for a bound that is a function of the mean (and so would cover the case where the mean is positive).



    I.e.



    $textPr left[ X > mathbbE[X] over 2 right] geq f(mathbbE[X]).$










    share|cite|improve this question











    $endgroup$














      1












      1








      1





      $begingroup$


      Consider a random variable $X$ that takes values between $-1$ and $1$. What is a non-trivial lower bound on the probability that the outcome of $X$ is greater than half of its mean?




      EDIT:



      I am looking for a bound that is a function of the mean (and so would cover the case where the mean is positive).



      I.e.



      $textPr left[ X > mathbbE[X] over 2 right] geq f(mathbbE[X]).$










      share|cite|improve this question











      $endgroup$




      Consider a random variable $X$ that takes values between $-1$ and $1$. What is a non-trivial lower bound on the probability that the outcome of $X$ is greater than half of its mean?




      EDIT:



      I am looking for a bound that is a function of the mean (and so would cover the case where the mean is positive).



      I.e.



      $textPr left[ X > mathbbE[X] over 2 right] geq f(mathbbE[X]).$







      probability probability-theory random-variables information-theory






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Mar 30 at 9:23







      user120404

















      asked Mar 29 at 22:34









      user120404user120404

      83118




      83118




















          2 Answers
          2






          active

          oldest

          votes


















          2












          $begingroup$

          Let $mu=E[X]$ and $Z = mathbb1_X > mu/2 $ (indicator variable), $a=P(Z=1)$



          We are seeking for the maximal $g(mu)$ such that $a ge g(mu)$



          If $mu < 0 $ then we cannot do better than the trivial $g(mu)=0$.



          (That can be seen by considering a Dirac delta on $x=mu$)



          For $mu >0$:



          $$
          mu = E[E[X | Z]]= a E[X| Z=1] + (1-a) E[X|Z=0] tag1
          $$



          but $E[X| Z=1] le 1$ (because $Xle 1$) and $E[X|Z=0] le mu/ 2$. Hence



          $$ mu le a + (1-a) mu /2 implies a ge fracmu2-mu tag2$$



          This bound is attained
          by two Dirac deltas on $x=mu/2$ and $x=1$ with weights $a$ and $1-a$ resp.
          Hence he desired bound is
          $$g(mu)=begincases
          0 & mule 0\
          fracmu2-mu & mu>0
          endcasestag3$$






          share|cite|improve this answer











          $endgroup$




















            2












            $begingroup$

            For this distribution the mean is near $-1$, so half the mean is $-1/2$, and clearly the probability of finding $x>-1/2$ can be made arbitrarily small.



            enter image description here






            share|cite|improve this answer









            $endgroup$












            • $begingroup$
              Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
              $endgroup$
              – user120404
              Mar 29 at 22:58







            • 1




              $begingroup$
              That wasn't your question. Please edit accordingly.
              $endgroup$
              – David G. Stork
              Mar 29 at 23:09










            • $begingroup$
              Please check the edited question.
              $endgroup$
              – user120404
              Mar 30 at 10:03











            Your Answer





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            2 Answers
            2






            active

            oldest

            votes








            2 Answers
            2






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2












            $begingroup$

            Let $mu=E[X]$ and $Z = mathbb1_X > mu/2 $ (indicator variable), $a=P(Z=1)$



            We are seeking for the maximal $g(mu)$ such that $a ge g(mu)$



            If $mu < 0 $ then we cannot do better than the trivial $g(mu)=0$.



            (That can be seen by considering a Dirac delta on $x=mu$)



            For $mu >0$:



            $$
            mu = E[E[X | Z]]= a E[X| Z=1] + (1-a) E[X|Z=0] tag1
            $$



            but $E[X| Z=1] le 1$ (because $Xle 1$) and $E[X|Z=0] le mu/ 2$. Hence



            $$ mu le a + (1-a) mu /2 implies a ge fracmu2-mu tag2$$



            This bound is attained
            by two Dirac deltas on $x=mu/2$ and $x=1$ with weights $a$ and $1-a$ resp.
            Hence he desired bound is
            $$g(mu)=begincases
            0 & mule 0\
            fracmu2-mu & mu>0
            endcasestag3$$






            share|cite|improve this answer











            $endgroup$

















              2












              $begingroup$

              Let $mu=E[X]$ and $Z = mathbb1_X > mu/2 $ (indicator variable), $a=P(Z=1)$



              We are seeking for the maximal $g(mu)$ such that $a ge g(mu)$



              If $mu < 0 $ then we cannot do better than the trivial $g(mu)=0$.



              (That can be seen by considering a Dirac delta on $x=mu$)



              For $mu >0$:



              $$
              mu = E[E[X | Z]]= a E[X| Z=1] + (1-a) E[X|Z=0] tag1
              $$



              but $E[X| Z=1] le 1$ (because $Xle 1$) and $E[X|Z=0] le mu/ 2$. Hence



              $$ mu le a + (1-a) mu /2 implies a ge fracmu2-mu tag2$$



              This bound is attained
              by two Dirac deltas on $x=mu/2$ and $x=1$ with weights $a$ and $1-a$ resp.
              Hence he desired bound is
              $$g(mu)=begincases
              0 & mule 0\
              fracmu2-mu & mu>0
              endcasestag3$$






              share|cite|improve this answer











              $endgroup$















                2












                2








                2





                $begingroup$

                Let $mu=E[X]$ and $Z = mathbb1_X > mu/2 $ (indicator variable), $a=P(Z=1)$



                We are seeking for the maximal $g(mu)$ such that $a ge g(mu)$



                If $mu < 0 $ then we cannot do better than the trivial $g(mu)=0$.



                (That can be seen by considering a Dirac delta on $x=mu$)



                For $mu >0$:



                $$
                mu = E[E[X | Z]]= a E[X| Z=1] + (1-a) E[X|Z=0] tag1
                $$



                but $E[X| Z=1] le 1$ (because $Xle 1$) and $E[X|Z=0] le mu/ 2$. Hence



                $$ mu le a + (1-a) mu /2 implies a ge fracmu2-mu tag2$$



                This bound is attained
                by two Dirac deltas on $x=mu/2$ and $x=1$ with weights $a$ and $1-a$ resp.
                Hence he desired bound is
                $$g(mu)=begincases
                0 & mule 0\
                fracmu2-mu & mu>0
                endcasestag3$$






                share|cite|improve this answer











                $endgroup$



                Let $mu=E[X]$ and $Z = mathbb1_X > mu/2 $ (indicator variable), $a=P(Z=1)$



                We are seeking for the maximal $g(mu)$ such that $a ge g(mu)$



                If $mu < 0 $ then we cannot do better than the trivial $g(mu)=0$.



                (That can be seen by considering a Dirac delta on $x=mu$)



                For $mu >0$:



                $$
                mu = E[E[X | Z]]= a E[X| Z=1] + (1-a) E[X|Z=0] tag1
                $$



                but $E[X| Z=1] le 1$ (because $Xle 1$) and $E[X|Z=0] le mu/ 2$. Hence



                $$ mu le a + (1-a) mu /2 implies a ge fracmu2-mu tag2$$



                This bound is attained
                by two Dirac deltas on $x=mu/2$ and $x=1$ with weights $a$ and $1-a$ resp.
                Hence he desired bound is
                $$g(mu)=begincases
                0 & mule 0\
                fracmu2-mu & mu>0
                endcasestag3$$







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited Mar 30 at 15:49

























                answered Mar 30 at 12:45









                leonbloyleonbloy

                42.2k647108




                42.2k647108





















                    2












                    $begingroup$

                    For this distribution the mean is near $-1$, so half the mean is $-1/2$, and clearly the probability of finding $x>-1/2$ can be made arbitrarily small.



                    enter image description here






                    share|cite|improve this answer









                    $endgroup$












                    • $begingroup$
                      Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                      $endgroup$
                      – user120404
                      Mar 29 at 22:58







                    • 1




                      $begingroup$
                      That wasn't your question. Please edit accordingly.
                      $endgroup$
                      – David G. Stork
                      Mar 29 at 23:09










                    • $begingroup$
                      Please check the edited question.
                      $endgroup$
                      – user120404
                      Mar 30 at 10:03















                    2












                    $begingroup$

                    For this distribution the mean is near $-1$, so half the mean is $-1/2$, and clearly the probability of finding $x>-1/2$ can be made arbitrarily small.



                    enter image description here






                    share|cite|improve this answer









                    $endgroup$












                    • $begingroup$
                      Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                      $endgroup$
                      – user120404
                      Mar 29 at 22:58







                    • 1




                      $begingroup$
                      That wasn't your question. Please edit accordingly.
                      $endgroup$
                      – David G. Stork
                      Mar 29 at 23:09










                    • $begingroup$
                      Please check the edited question.
                      $endgroup$
                      – user120404
                      Mar 30 at 10:03













                    2












                    2








                    2





                    $begingroup$

                    For this distribution the mean is near $-1$, so half the mean is $-1/2$, and clearly the probability of finding $x>-1/2$ can be made arbitrarily small.



                    enter image description here






                    share|cite|improve this answer









                    $endgroup$



                    For this distribution the mean is near $-1$, so half the mean is $-1/2$, and clearly the probability of finding $x>-1/2$ can be made arbitrarily small.



                    enter image description here







                    share|cite|improve this answer












                    share|cite|improve this answer



                    share|cite|improve this answer










                    answered Mar 29 at 22:45









                    David G. StorkDavid G. Stork

                    12k41735




                    12k41735











                    • $begingroup$
                      Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                      $endgroup$
                      – user120404
                      Mar 29 at 22:58







                    • 1




                      $begingroup$
                      That wasn't your question. Please edit accordingly.
                      $endgroup$
                      – David G. Stork
                      Mar 29 at 23:09










                    • $begingroup$
                      Please check the edited question.
                      $endgroup$
                      – user120404
                      Mar 30 at 10:03
















                    • $begingroup$
                      Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                      $endgroup$
                      – user120404
                      Mar 29 at 22:58







                    • 1




                      $begingroup$
                      That wasn't your question. Please edit accordingly.
                      $endgroup$
                      – David G. Stork
                      Mar 29 at 23:09










                    • $begingroup$
                      Please check the edited question.
                      $endgroup$
                      – user120404
                      Mar 30 at 10:03















                    $begingroup$
                    Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                    $endgroup$
                    – user120404
                    Mar 29 at 22:58





                    $begingroup$
                    Yes thank you, but is there an expression for the lower bound as a function of the mean (which would cover the cases in which the mean is positive)?
                    $endgroup$
                    – user120404
                    Mar 29 at 22:58





                    1




                    1




                    $begingroup$
                    That wasn't your question. Please edit accordingly.
                    $endgroup$
                    – David G. Stork
                    Mar 29 at 23:09




                    $begingroup$
                    That wasn't your question. Please edit accordingly.
                    $endgroup$
                    – David G. Stork
                    Mar 29 at 23:09












                    $begingroup$
                    Please check the edited question.
                    $endgroup$
                    – user120404
                    Mar 30 at 10:03




                    $begingroup$
                    Please check the edited question.
                    $endgroup$
                    – user120404
                    Mar 30 at 10:03

















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