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Guidelines_English_Final
تحميل الدليل التدريبي

أسئلة شائعة


 

A Course Identification and General Information

1.  Course title and code Elements of Distribution Theory  Stat 111

2.  Credit hours 3

3.  Program(s) in which the course is offered.

(If general elective available in many programs indicate this rather than list programs)

College of Computer Science

4.  Name of faculty member responsible for the course Dr.Moshira Ismail  Dr.Nahed Helmy 

 

5.  Level/year at which this course is offered  l

6.  Pre-requisites for this course (if any)  none   St at 111 or 324

 

7.  Co-requisites for this course (if any)  none

 

8.  Location if not on main campus

 

 


B  Objectives 

1.  Summary of the main learning outcomes for students enrolled in the course.

*Acquiring Knowledge of some methods of combinatory, some concepts of probability ,Bayes theorem ,random variables probability distributions expectations variances and moment generating functions ce. 

*Acquiring cognitive skills through thinking ,problem solving and applying statistical tools..

*Acquiring numerical skills through computational work done in solving problems. 

*Acquiring  interpersonal  and responsibility skills through discussions and solving assignments

2.       Briefly describe any plans for developing and improving the course that are being implemented.  (eg increased use of IT or web based reference material,  changes in content as a result of new research in the field)

.

SAS  statistical package will be applied  in teaching parts of the course.

 

 

 

 

 

 

C.  Course Description  (Note:  General description in the form to be used for the Bulletin or Handbook should be attached)

 

1 Topics to be Covered

 

Topic

No of

Weeks

Contacthours

 

Sets theory and Combinatorial

 

 

3

 

    6

 

Probability and Bayes Theorem

 

     3             

 

     6

 

Random Variables

 

 

     1     

 

    2

 

  Probability  Distributions

 

 

     3         

 

   6

 

Joint Probability Distributions                                                                                                           

 

 

     1.5

 

   3

 

Functions of Random Variables

 

 

 

     1

 

    2  

Expectations, variances and moment generating function

 

    2.5

5

 

2 Course components (total contact hours per semester):                         

Lecture:

Credit hours: 45

Actual hours:30

 

Tutorial: 

Credit hours:15

Actual hours:30

Practical/Fieldwork/Internship:

 

Other:

 

3. Additional private study/learning hours expected for students per week. (This should be an average :for the semester not a specific requirement in each week)

             45     hours

 

4. Development of Learning Outcomes in Domains of Learning 

For each of the domains of learning shown below indicate:

·         A brief summary of the knowledge or skill the course is intended to develop;

·         A description of the teaching strategies to be used in the course to develop that knowledge or  skill;

·         The methods of student assessment to be used in the course to evaluate learning outcomes in the domain concerned.

a.  Knowledge 

(i)  Description of the knowledge to be acquired

*Knowing some probability concepts

*Knowing some principle of combinatorial

*Knowing Bayes Theorem

 

*Knowing the concept of random variables

 

*.Knowing some  single and joint probability distributions and some related  measures

 

 

 

(ii)  Teaching strategies to be used to develop that knowledge

*Lectures and tutorials.

*Participation of students through discussions.

*Solving homework which is  given to students in the tutorials.

 

 

(iii)  Methods of assessment of knowledge acquired

assignments and exams

 

b.  Cognitive Skills

(i)  Cognitive skills to be developed

*skills of how to apply the knowledge students have acquired   about probability ,random variables and probability distributions  in solving real life problems .

 

 

 

(ii)  Teaching strategies to be used to develop these cognitive skills

 

*lectures and tutorials followed by numerical examples

* engaging students in discussions during lectures and tutorials

 

 

 

(iii)  Methods of assessment of students cognitive skills

Exams and assignments involve problems which require critical thinking to test the skills of   students to  apply the knowledge they have acquired

 

 

 

c. Interpersonal Skills and Responsibility

 

(i)  Description of the interpersonal skills and capacity to carry responsibility to be developed

Punctual attendance of classes is required in lectures and tutorials.

 

Students learn to organise their time properly in studying the course.

 

 

 

(ii)                 Teaching strategies to be used to develop these skills and abilities

*students are required to solve assignments after each tutorial and are given a time limit for handing them.

*students are encouraged to participate in class discussions.

 

 

 

 

(iii)  Methods of assessment of students interpersonal skills and capacity to carry responsibility

*class attendance is recorded.

 

d.   Communication, Information Technology and Numerical Skills

(i)  Description of the skills to be developed in this domain.

*computational skills through solving problems

 

 

 

(ii)  Teaching strategies to be used to develop these skills

 

 

 

(iii)  Methods of assessment of students numerical and communication skills

 

 

e.  Psychomotor Skills (if applicable)not applicable

(i)  Description of the psychomotor skills to be developed and the level of performance required

 

 

 

(ii)  Teaching strategies to be used to develop these skills

 

 

 

(iii)  Methods of assessment of students psychomotor skills

 

 

 

 


 

 

5. Schedule of Assessment Tasks for Students During the Semester

 

Assessment

Assessment task  (eg. essay, test, group project, examination etc.)

Week due

Proportion of Final Assessment

1

 

 

First Midterm examination                                                                                

 

        7

 

20%

2

 

 

Second Midterm examination

 

         11           

 

20%

3

 

 

Final examination

 

As scheduled by registrar   

 

60%

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