poisson distribution probability problem












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$begingroup$


I am working on a Poisson distribution problem stated in the main question and got stuck and do not know how to proceed as I did not understand the next question on how to work it out



The following data collected from the Australian Bureau of Meteorology Website (http://tinypic.com/r/2ibi9gi/8) gives the daily rainfall data for the year 2014 in Sydney in mm I have also calculated the mean and std deviation for each month



Can someone check my work ? for the part a (i) and (ii)



a) (i) What is the probability that on any given week in a year there would be no rainfall?(Poisson)
In 52 weeks, we 131 rainy days (mean summation for year 2014)
Therefore, in one week, it rain γyear= 131/364, γwk= γyear/52
Furthermore, P(X=0)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^0 e^(-(γyear/52)))/0!=0.993

(ii)What is the probability that there will be 2 or more days of rainfall in a week? (There are 52 weeks in a year and a week is assumed to start from Monday).
In a similar manner, P(X≥2)=1-P(X<2)=1-(P(0)-P(1))
Furthermore, P(X=1)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^1 e^(-(γyear/52)))/1!=0.0069

With the mentioned formula, for P(X≥2)=1-0.993-0.0069=0.0139



I did not understand how to proceed with the following part



(b) Assuming that the weekly total amount of rainfall from the data provided in part (a) has a normal distribution, compute the mean and standard deviation of weekly totals.



(i) What is the probability that in a given week there will be between 4 mm and 12 mm of rainfall?



(ii) What is the amount of rainfall if only 8% of the weeks have that amount of rainfall or higher?



thank you and much appreciated



as mentioned in the answer for question ii)



In 365 days, it rains 32.62206 mm (mean summation for year 2014)
Therefore, in one day, it rains 32.62206/365



mean = 32.62206/365
Poisson distribution with mean 32.62206/365.
P(no rain) = P(x=0) = e^-(32.62206/365) (32.62206/365)^0 /0! = e^(-32.62206/365) =P= 0.914

When using a Binomial with 7 trials x>=2 successes and a probability of 1-0.914 the answer obtained is P(X>=2) = 0.00349


from the following: http://stattrek.com/online-calculator/poisson.aspx










share|cite|improve this question











$endgroup$

















    0












    $begingroup$


    I am working on a Poisson distribution problem stated in the main question and got stuck and do not know how to proceed as I did not understand the next question on how to work it out



    The following data collected from the Australian Bureau of Meteorology Website (http://tinypic.com/r/2ibi9gi/8) gives the daily rainfall data for the year 2014 in Sydney in mm I have also calculated the mean and std deviation for each month



    Can someone check my work ? for the part a (i) and (ii)



    a) (i) What is the probability that on any given week in a year there would be no rainfall?(Poisson)
    In 52 weeks, we 131 rainy days (mean summation for year 2014)
    Therefore, in one week, it rain γyear= 131/364, γwk= γyear/52
    Furthermore, P(X=0)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^0 e^(-(γyear/52)))/0!=0.993

    (ii)What is the probability that there will be 2 or more days of rainfall in a week? (There are 52 weeks in a year and a week is assumed to start from Monday).
    In a similar manner, P(X≥2)=1-P(X<2)=1-(P(0)-P(1))
    Furthermore, P(X=1)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^1 e^(-(γyear/52)))/1!=0.0069

    With the mentioned formula, for P(X≥2)=1-0.993-0.0069=0.0139



    I did not understand how to proceed with the following part



    (b) Assuming that the weekly total amount of rainfall from the data provided in part (a) has a normal distribution, compute the mean and standard deviation of weekly totals.



    (i) What is the probability that in a given week there will be between 4 mm and 12 mm of rainfall?



    (ii) What is the amount of rainfall if only 8% of the weeks have that amount of rainfall or higher?



    thank you and much appreciated



    as mentioned in the answer for question ii)



    In 365 days, it rains 32.62206 mm (mean summation for year 2014)
    Therefore, in one day, it rains 32.62206/365



    mean = 32.62206/365
    Poisson distribution with mean 32.62206/365.
    P(no rain) = P(x=0) = e^-(32.62206/365) (32.62206/365)^0 /0! = e^(-32.62206/365) =P= 0.914

    When using a Binomial with 7 trials x>=2 successes and a probability of 1-0.914 the answer obtained is P(X>=2) = 0.00349


    from the following: http://stattrek.com/online-calculator/poisson.aspx










    share|cite|improve this question











    $endgroup$















      0












      0








      0





      $begingroup$


      I am working on a Poisson distribution problem stated in the main question and got stuck and do not know how to proceed as I did not understand the next question on how to work it out



      The following data collected from the Australian Bureau of Meteorology Website (http://tinypic.com/r/2ibi9gi/8) gives the daily rainfall data for the year 2014 in Sydney in mm I have also calculated the mean and std deviation for each month



      Can someone check my work ? for the part a (i) and (ii)



      a) (i) What is the probability that on any given week in a year there would be no rainfall?(Poisson)
      In 52 weeks, we 131 rainy days (mean summation for year 2014)
      Therefore, in one week, it rain γyear= 131/364, γwk= γyear/52
      Furthermore, P(X=0)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^0 e^(-(γyear/52)))/0!=0.993

      (ii)What is the probability that there will be 2 or more days of rainfall in a week? (There are 52 weeks in a year and a week is assumed to start from Monday).
      In a similar manner, P(X≥2)=1-P(X<2)=1-(P(0)-P(1))
      Furthermore, P(X=1)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^1 e^(-(γyear/52)))/1!=0.0069

      With the mentioned formula, for P(X≥2)=1-0.993-0.0069=0.0139



      I did not understand how to proceed with the following part



      (b) Assuming that the weekly total amount of rainfall from the data provided in part (a) has a normal distribution, compute the mean and standard deviation of weekly totals.



      (i) What is the probability that in a given week there will be between 4 mm and 12 mm of rainfall?



      (ii) What is the amount of rainfall if only 8% of the weeks have that amount of rainfall or higher?



      thank you and much appreciated



      as mentioned in the answer for question ii)



      In 365 days, it rains 32.62206 mm (mean summation for year 2014)
      Therefore, in one day, it rains 32.62206/365



      mean = 32.62206/365
      Poisson distribution with mean 32.62206/365.
      P(no rain) = P(x=0) = e^-(32.62206/365) (32.62206/365)^0 /0! = e^(-32.62206/365) =P= 0.914

      When using a Binomial with 7 trials x>=2 successes and a probability of 1-0.914 the answer obtained is P(X>=2) = 0.00349


      from the following: http://stattrek.com/online-calculator/poisson.aspx










      share|cite|improve this question











      $endgroup$




      I am working on a Poisson distribution problem stated in the main question and got stuck and do not know how to proceed as I did not understand the next question on how to work it out



      The following data collected from the Australian Bureau of Meteorology Website (http://tinypic.com/r/2ibi9gi/8) gives the daily rainfall data for the year 2014 in Sydney in mm I have also calculated the mean and std deviation for each month



      Can someone check my work ? for the part a (i) and (ii)



      a) (i) What is the probability that on any given week in a year there would be no rainfall?(Poisson)
      In 52 weeks, we 131 rainy days (mean summation for year 2014)
      Therefore, in one week, it rain γyear= 131/364, γwk= γyear/52
      Furthermore, P(X=0)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^0 e^(-(γyear/52)))/0!=0.993

      (ii)What is the probability that there will be 2 or more days of rainfall in a week? (There are 52 weeks in a year and a week is assumed to start from Monday).
      In a similar manner, P(X≥2)=1-P(X<2)=1-(P(0)-P(1))
      Furthermore, P(X=1)= (γ^X×e^(-γ))/γ!= (〖(γyear/52)〗^1 e^(-(γyear/52)))/1!=0.0069

      With the mentioned formula, for P(X≥2)=1-0.993-0.0069=0.0139



      I did not understand how to proceed with the following part



      (b) Assuming that the weekly total amount of rainfall from the data provided in part (a) has a normal distribution, compute the mean and standard deviation of weekly totals.



      (i) What is the probability that in a given week there will be between 4 mm and 12 mm of rainfall?



      (ii) What is the amount of rainfall if only 8% of the weeks have that amount of rainfall or higher?



      thank you and much appreciated



      as mentioned in the answer for question ii)



      In 365 days, it rains 32.62206 mm (mean summation for year 2014)
      Therefore, in one day, it rains 32.62206/365



      mean = 32.62206/365
      Poisson distribution with mean 32.62206/365.
      P(no rain) = P(x=0) = e^-(32.62206/365) (32.62206/365)^0 /0! = e^(-32.62206/365) =P= 0.914

      When using a Binomial with 7 trials x>=2 successes and a probability of 1-0.914 the answer obtained is P(X>=2) = 0.00349


      from the following: http://stattrek.com/online-calculator/poisson.aspx







      probability statistics matlab poisson-distribution






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      share|cite|improve this question








      edited Sep 6 '15 at 22:13







      chaosmind

















      asked Sep 4 '15 at 10:38









      chaosmindchaosmind

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          1 Answer
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          $begingroup$

          (a.ii) In a similar manner, find the probability that there will be no rain on any given day; call this $p$.   The count of rainy days in a week will be Binomially distributed. $Rsimmathcal {Bin}(7, 1-p)$



          (b) If we assume no seasonal influence, then the yearly rainfall amount is the sum of 52 independent and identically distributed weekly rainfall amounts.   The weekly rainfall amounts are approximated to be normally distributed.   The sum of independent normally distributed random variables is a normally distributed random variable whose (1) mean is the sum of means and (2) variance is the sum of variances.   You have the mean and variance of the yearly rainfall amount.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
            $endgroup$
            – chaosmind
            Sep 4 '15 at 23:01










          • $begingroup$
            and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
            $endgroup$
            – chaosmind
            Sep 5 '15 at 20:06












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          1 Answer
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          active

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          0












          $begingroup$

          (a.ii) In a similar manner, find the probability that there will be no rain on any given day; call this $p$.   The count of rainy days in a week will be Binomially distributed. $Rsimmathcal {Bin}(7, 1-p)$



          (b) If we assume no seasonal influence, then the yearly rainfall amount is the sum of 52 independent and identically distributed weekly rainfall amounts.   The weekly rainfall amounts are approximated to be normally distributed.   The sum of independent normally distributed random variables is a normally distributed random variable whose (1) mean is the sum of means and (2) variance is the sum of variances.   You have the mean and variance of the yearly rainfall amount.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
            $endgroup$
            – chaosmind
            Sep 4 '15 at 23:01










          • $begingroup$
            and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
            $endgroup$
            – chaosmind
            Sep 5 '15 at 20:06
















          0












          $begingroup$

          (a.ii) In a similar manner, find the probability that there will be no rain on any given day; call this $p$.   The count of rainy days in a week will be Binomially distributed. $Rsimmathcal {Bin}(7, 1-p)$



          (b) If we assume no seasonal influence, then the yearly rainfall amount is the sum of 52 independent and identically distributed weekly rainfall amounts.   The weekly rainfall amounts are approximated to be normally distributed.   The sum of independent normally distributed random variables is a normally distributed random variable whose (1) mean is the sum of means and (2) variance is the sum of variances.   You have the mean and variance of the yearly rainfall amount.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
            $endgroup$
            – chaosmind
            Sep 4 '15 at 23:01










          • $begingroup$
            and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
            $endgroup$
            – chaosmind
            Sep 5 '15 at 20:06














          0












          0








          0





          $begingroup$

          (a.ii) In a similar manner, find the probability that there will be no rain on any given day; call this $p$.   The count of rainy days in a week will be Binomially distributed. $Rsimmathcal {Bin}(7, 1-p)$



          (b) If we assume no seasonal influence, then the yearly rainfall amount is the sum of 52 independent and identically distributed weekly rainfall amounts.   The weekly rainfall amounts are approximated to be normally distributed.   The sum of independent normally distributed random variables is a normally distributed random variable whose (1) mean is the sum of means and (2) variance is the sum of variances.   You have the mean and variance of the yearly rainfall amount.






          share|cite|improve this answer











          $endgroup$



          (a.ii) In a similar manner, find the probability that there will be no rain on any given day; call this $p$.   The count of rainy days in a week will be Binomially distributed. $Rsimmathcal {Bin}(7, 1-p)$



          (b) If we assume no seasonal influence, then the yearly rainfall amount is the sum of 52 independent and identically distributed weekly rainfall amounts.   The weekly rainfall amounts are approximated to be normally distributed.   The sum of independent normally distributed random variables is a normally distributed random variable whose (1) mean is the sum of means and (2) variance is the sum of variances.   You have the mean and variance of the yearly rainfall amount.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Sep 4 '15 at 14:47

























          answered Sep 4 '15 at 14:40









          Graham KempGraham Kemp

          87.9k43578




          87.9k43578












          • $begingroup$
            great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
            $endgroup$
            – chaosmind
            Sep 4 '15 at 23:01










          • $begingroup$
            and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
            $endgroup$
            – chaosmind
            Sep 5 '15 at 20:06


















          • $begingroup$
            great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
            $endgroup$
            – chaosmind
            Sep 4 '15 at 23:01










          • $begingroup$
            and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
            $endgroup$
            – chaosmind
            Sep 5 '15 at 20:06
















          $begingroup$
          great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
          $endgroup$
          – chaosmind
          Sep 4 '15 at 23:01




          $begingroup$
          great thank you I will work that out :D didn't work with the binomial distr so I did not know it can be done in such a way
          $endgroup$
          – chaosmind
          Sep 4 '15 at 23:01












          $begingroup$
          and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
          $endgroup$
          – chaosmind
          Sep 5 '15 at 20:06




          $begingroup$
          and is the mean and standard deviation of weekly totals the same as the ones I calculated or I have to divide by the number of weeks in a month for each month
          $endgroup$
          – chaosmind
          Sep 5 '15 at 20:06


















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