Topic outline

  • General

    Course Objectives

    Represent uncertainty using Probability and Statistics

    Characterize uncertainty using random processes

    Course Outcomes:

    Upon completion of this course the student will be able to:

    • CO1: Apply the knowledge of basics of probability and random variable theory to represent uncertainty

    • CO2: Analyze uncertainty using statistics of a random variable

    • CO3: Characterize uncertainty using pairs of random variables

    • CO4: Develop matrix notation to represent and analyze multidimensional random variables

    • CO5: Characterize real world information using Random processes.

    • (Knowledge levels : L1:Remembering, L2: Understanding, L3: Applying, L4:Analyzing, L5:Evaluating, L6:Creating)CO1:

    Mapping of Course Outcomes (cOs) to Program Outcomes (POs) & Program Specific Outcomes (PSOs)


    POs

    PSOs


    1

    2

    3

    4

    5

    6

    7

    8

    9

    10

    11

    12

    1

    2

    3

    COs

    CO1

    3

    2

     

     


     

     

     


     

     


    3

     


    CO2

    2

    2

     

     


     

     

     

    2

     

     


    2

    2


    CO3

    2

    2


     


     

     

     

    2

     

     


    2

    2


    CO4

    2

    2


     


     

     

     

    2

     

     


    2

    2


    CO5

    2

    2

    2

     


     

     

     

    2

     

     


    2

    2


    CO6


















    Assessment Tools

    COs

    Direct AT

    CO1

    CO2

    CO3

    CO4

    CO5

    CO6

    CIE (Individual)


    SEE (Individual)


    Assignments (Individual/Group)


    Micro Projects (Group)







    Topic seminar (Individual)


    Case studies (Individual/Group)







    Online courses (Individual)







    Indirect AT







    Course end survey (Students)


    Student profile (Faculty)









  • Introduction

    In this Module, basics of probability, notion of joint and conditional probability leading to total probability and Bayes's theorem is discussed.

  • Discrete randomvariable

  • Continuous Random Variable

    Discussion on PDF, CDF, commonly used continuous random variables

  • Topic 5

    • Topic 6

      • Topic 7

        • Topic 8

          • Topic 9

            • Topic 10

              • Topic 11

                • Topic 12

                  • Topic 13

                    • Topic 14

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                                  • Topic 21

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