Convergence in probability towards a constant












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Prove that if a sequence $X_1,X_2..$ of random variables satisfies the following conditions: $$1.lim_{ntoinfty}mathbb{E}(X_n)=a,space ainmathbb{R}$$
$$2.lim_{ntoinfty}mathbb{V}(X_n)=0$$
Then this sequence converges in probability towards $a$: $$lim_{ntoinfty}mathbb{P}(|X_n-a|geqepsilon) = 0$$










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    -1












    $begingroup$


    Prove that if a sequence $X_1,X_2..$ of random variables satisfies the following conditions: $$1.lim_{ntoinfty}mathbb{E}(X_n)=a,space ainmathbb{R}$$
    $$2.lim_{ntoinfty}mathbb{V}(X_n)=0$$
    Then this sequence converges in probability towards $a$: $$lim_{ntoinfty}mathbb{P}(|X_n-a|geqepsilon) = 0$$










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      -1












      -1








      -1





      $begingroup$


      Prove that if a sequence $X_1,X_2..$ of random variables satisfies the following conditions: $$1.lim_{ntoinfty}mathbb{E}(X_n)=a,space ainmathbb{R}$$
      $$2.lim_{ntoinfty}mathbb{V}(X_n)=0$$
      Then this sequence converges in probability towards $a$: $$lim_{ntoinfty}mathbb{P}(|X_n-a|geqepsilon) = 0$$










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      $endgroup$




      Prove that if a sequence $X_1,X_2..$ of random variables satisfies the following conditions: $$1.lim_{ntoinfty}mathbb{E}(X_n)=a,space ainmathbb{R}$$
      $$2.lim_{ntoinfty}mathbb{V}(X_n)=0$$
      Then this sequence converges in probability towards $a$: $$lim_{ntoinfty}mathbb{P}(|X_n-a|geqepsilon) = 0$$







      convergence probability-limit-theorems expected-value






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      asked Jan 11 at 23:29









      AromaTheLoopAromaTheLoop

      444




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          2 Answers
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          $begingroup$

          Fix $varepsilon>0$. Note that
          $$
          |X_n-a|leq |X_n-EX_n|+|EX_n-a|
          $$

          whence
          $$
          P(|X_n-a|gevarepsilon)leq P(|X_n-EX_n|gevarepsilon/2)+P(|EX_n-a|gevarepsilon/2) tag{1}
          $$

          The first term on the RHS of (1) goes to zero by the assumption that $text{Var}(X_n)to 0$ combined with Chebeshev's inequality. The second term on the RHS of (1) goes to zero by the assumption that $EX_nto a$ .






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            $begingroup$

            $E(X_n-a)^{2}=EX_n^{2}+a^{2}-2aEX_n =var(X_n)+(EX_n)^{2}+a^{2}-2aEX_n to 0+a^{2}+a^{2}-2a^{2}=0$. Hence $P{|X_n-a| geq epsilon} leq frac {E(X_n-a)^{2}} {epsilon^{2}} to 0$.






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              2 Answers
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              2 Answers
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              1












              $begingroup$

              Fix $varepsilon>0$. Note that
              $$
              |X_n-a|leq |X_n-EX_n|+|EX_n-a|
              $$

              whence
              $$
              P(|X_n-a|gevarepsilon)leq P(|X_n-EX_n|gevarepsilon/2)+P(|EX_n-a|gevarepsilon/2) tag{1}
              $$

              The first term on the RHS of (1) goes to zero by the assumption that $text{Var}(X_n)to 0$ combined with Chebeshev's inequality. The second term on the RHS of (1) goes to zero by the assumption that $EX_nto a$ .






              share|cite|improve this answer









              $endgroup$


















                1












                $begingroup$

                Fix $varepsilon>0$. Note that
                $$
                |X_n-a|leq |X_n-EX_n|+|EX_n-a|
                $$

                whence
                $$
                P(|X_n-a|gevarepsilon)leq P(|X_n-EX_n|gevarepsilon/2)+P(|EX_n-a|gevarepsilon/2) tag{1}
                $$

                The first term on the RHS of (1) goes to zero by the assumption that $text{Var}(X_n)to 0$ combined with Chebeshev's inequality. The second term on the RHS of (1) goes to zero by the assumption that $EX_nto a$ .






                share|cite|improve this answer









                $endgroup$
















                  1












                  1








                  1





                  $begingroup$

                  Fix $varepsilon>0$. Note that
                  $$
                  |X_n-a|leq |X_n-EX_n|+|EX_n-a|
                  $$

                  whence
                  $$
                  P(|X_n-a|gevarepsilon)leq P(|X_n-EX_n|gevarepsilon/2)+P(|EX_n-a|gevarepsilon/2) tag{1}
                  $$

                  The first term on the RHS of (1) goes to zero by the assumption that $text{Var}(X_n)to 0$ combined with Chebeshev's inequality. The second term on the RHS of (1) goes to zero by the assumption that $EX_nto a$ .






                  share|cite|improve this answer









                  $endgroup$



                  Fix $varepsilon>0$. Note that
                  $$
                  |X_n-a|leq |X_n-EX_n|+|EX_n-a|
                  $$

                  whence
                  $$
                  P(|X_n-a|gevarepsilon)leq P(|X_n-EX_n|gevarepsilon/2)+P(|EX_n-a|gevarepsilon/2) tag{1}
                  $$

                  The first term on the RHS of (1) goes to zero by the assumption that $text{Var}(X_n)to 0$ combined with Chebeshev's inequality. The second term on the RHS of (1) goes to zero by the assumption that $EX_nto a$ .







                  share|cite|improve this answer












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                  share|cite|improve this answer










                  answered Jan 12 at 0:08









                  Foobaz JohnFoobaz John

                  22.1k41352




                  22.1k41352























                      0












                      $begingroup$

                      $E(X_n-a)^{2}=EX_n^{2}+a^{2}-2aEX_n =var(X_n)+(EX_n)^{2}+a^{2}-2aEX_n to 0+a^{2}+a^{2}-2a^{2}=0$. Hence $P{|X_n-a| geq epsilon} leq frac {E(X_n-a)^{2}} {epsilon^{2}} to 0$.






                      share|cite|improve this answer









                      $endgroup$


















                        0












                        $begingroup$

                        $E(X_n-a)^{2}=EX_n^{2}+a^{2}-2aEX_n =var(X_n)+(EX_n)^{2}+a^{2}-2aEX_n to 0+a^{2}+a^{2}-2a^{2}=0$. Hence $P{|X_n-a| geq epsilon} leq frac {E(X_n-a)^{2}} {epsilon^{2}} to 0$.






                        share|cite|improve this answer









                        $endgroup$
















                          0












                          0








                          0





                          $begingroup$

                          $E(X_n-a)^{2}=EX_n^{2}+a^{2}-2aEX_n =var(X_n)+(EX_n)^{2}+a^{2}-2aEX_n to 0+a^{2}+a^{2}-2a^{2}=0$. Hence $P{|X_n-a| geq epsilon} leq frac {E(X_n-a)^{2}} {epsilon^{2}} to 0$.






                          share|cite|improve this answer









                          $endgroup$



                          $E(X_n-a)^{2}=EX_n^{2}+a^{2}-2aEX_n =var(X_n)+(EX_n)^{2}+a^{2}-2aEX_n to 0+a^{2}+a^{2}-2a^{2}=0$. Hence $P{|X_n-a| geq epsilon} leq frac {E(X_n-a)^{2}} {epsilon^{2}} to 0$.







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                          share|cite|improve this answer



                          share|cite|improve this answer










                          answered Jan 11 at 23:33









                          Kavi Rama MurthyKavi Rama Murthy

                          59.1k42161




                          59.1k42161






























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