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Quantitative Methods I: Section B & C
                 (COMPUTER) ASSIGNMENT - II

Due on or before: 6 pm on July 16, 2012
   1. Describe real-life examples of TWO random variables, one whose distribution
      can be modeled as a Binomial distribution and the other whose distribution is
      discrete but should NOT modeled as Binomial. Reflect on assumptions made
      while modeling in each case. Calculate probabilities of at least one event, of your
      choice, in each case based on your models.

   2. Open the template Bayesian Revision, using the CD-ROM accompanied by the
      text-book (also copied in moodle). This macro exhibits how prior probabilities get
      updated with additional information using the Bayes’ theorem.
          a. Select a range for p in (0,1) consisting 8-12 values.
          b. Put a valid prior distribution on this.
          c. Now consider a specific response from a pilot survey -- in terms of x
             positive responses out of a random selection of n; [Choose your x and n].
          d. Reflect on posterior distribution that you get.

Rules for submission: Your submitted file should be named “ROLLNO_CE2.ext” where
“ROLLNO” is your PGP roll number and “.ext” would reflect the software you are using. The
file needs to be submitted via moodle. e-mail submissions would
not be considered under any circumstances.




                                           1

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Exercise 2

  • 1. Quantitative Methods I: Section B & C (COMPUTER) ASSIGNMENT - II Due on or before: 6 pm on July 16, 2012 1. Describe real-life examples of TWO random variables, one whose distribution can be modeled as a Binomial distribution and the other whose distribution is discrete but should NOT modeled as Binomial. Reflect on assumptions made while modeling in each case. Calculate probabilities of at least one event, of your choice, in each case based on your models. 2. Open the template Bayesian Revision, using the CD-ROM accompanied by the text-book (also copied in moodle). This macro exhibits how prior probabilities get updated with additional information using the Bayes’ theorem. a. Select a range for p in (0,1) consisting 8-12 values. b. Put a valid prior distribution on this. c. Now consider a specific response from a pilot survey -- in terms of x positive responses out of a random selection of n; [Choose your x and n]. d. Reflect on posterior distribution that you get. Rules for submission: Your submitted file should be named “ROLLNO_CE2.ext” where “ROLLNO” is your PGP roll number and “.ext” would reflect the software you are using. The file needs to be submitted via moodle. e-mail submissions would not be considered under any circumstances. 1