Academic Department : Mathematics. Programme : Course

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Institution :

. College of Science.

Academic Department :

Mathematics

.

Programme :

Mathematics

.

Course : .

Statistics and Probability (2)

.

STAT 302

.

Course Coordinator : ... ...

Programme Coordinator : ...

Course Specification Approved Date : …./ … / …… H

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A. Course Identification and General Information

1 -

Course title :

Statistics and Probability (2)

Course Code:

^{STAT 302}

. 2. Credit hours : (

^{4 Hours}

)

3 - Program(s) in which the course is offered:

Mathematics

4 – Course Language :

^English

5 - Name of faculty member responsible for the course:

M.EL-Shahat EL-Saadani

6 - Level/year at which this course is offered :

The sixth level

7 - Pre-requisites for this course (if any) :

 STAT 201

8 - Co-requisites for this course (if any) :

9 - Location if not on main campus :

Main Campus , Zulfi city

) (

10 - Mode of Instruction (mark all that apply)

A - Traditional classroom

What percentage? 90 %

B - Blended

(traditional and online) What percentage? ……. %

D - e-learning

What percentage? ……. %

E - Correspondence

What percentage? ……. %

F - Other

What percentage? 10 %

Comments :

...

B Objectives

What is the main purpose for this course?

...

Briefly describe any plans for developing and improving the course that are being implemented :

1. Define statistics, population and sample. Understand the statistic and the parameter 2. Determine probabilities from probability mass functions and the reverse

3. Understand the assumptions for each of the discrete probability distributions presented.

4. Select an appropriate discrete probability distribution to calculate probabilities in specific applications

5. Approximate probabilities for some binomial and Poisson distributions

6. Deduce the sampling distribution of the sample mean and show that it is unbiased estimator of the population mean.

.

... ... ... ...

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C. Course Description 1. Topics to be Covered

List of Topics No. of

Weeks

Contact Hours

Introduction and overview of Definition of the probability- Definition of

the random variable – the probability function of the discrete random variable - the density probability function of the continuous random variable

2 8

The Expectation and the variance of the random variable (Discrete and Continuous)

3 12

Discrete probability Distributions (Bernoulli, Binomial and Poisson) 3 12 Continuous probability distribution (Normal distribution and its

application). - Approximate probabilities for some binomial and Poisson distributions.

2 8

Other probability distributions: uniform, exponential, and gamma distributions.

3 12

- functions of random variables- mathematical expectation- the moment generating function. . Sampling distributions

2 8

2. Course components (total contact hours and credits per semester):

Lecture Tutorial Laboratory Practical Other: Total

Contact

Hours

45 30 0

...

45 120

Credit

45 15 0

...

0 50

3. Additional private study/learning hours expected for

students per week.

²

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4. Course Learning Outcomes in NQF Domains of Learning and Alignment with Assessment Methods and Teaching Strategy

NQF Learning Domains And Course Learning Outcomes

Course Teaching Strategies

Course Assessment

Methods

1.0 Knowledge

1.1

Define statistics, population and sample. Understand the statistic and the parameter.

List the addition and the multiplication rules of probability

Start each chapter by general idea and the benefit of it.

Demonstrate the course information and principles

through lectures.

Exams Midterms Final

examination.

1.2

Outline the logical thinking.

Determine probabilities from probability mass functions and the reverse.

Provide main ways to deal with the exercises.

Home work.

1.3

State the conditions of probability mass function. Solve some examples during the lecture.

Continuous discussions with the students during the lectures.

1.4 ... ... ...

2.0 Cognitive Skills

2.1

Deduce the sampling distribution of the sample mean.

The students will estimate the population parameter by the statistic

Encourage the student to look for some complicated problems in the different

references.

Midterm exams Quizzes.

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NQF Learning Domains And Course Learning Outcomes

Methods

2.2

Approximate probabilities for some binomial and Poisson

distributions

Understand the assumptions for each of the discrete probability distributions presented.

Ask the student to attend

lectures for practice solving problem.

Doing homework.

Check the problems solution.

2.3

Student's ability to write the properties of the mathematical expectation and the variance of X.

Homework assignments.

Discussion of how to simplify or analyses some problems using tree diagram

2.4 ... ... ...

3.0 Interpersonal Skills & Responsibility

3.1

The student should illustrate how take up responsibility. Ask the students to search the internet and use the library.

Encourage them how to attend lectures

regularly by assigning marks for attendance.

Quizzes of some previous

lectures.

Ask the absent students about last lecture.

3.2

Must be shown the ability of working independently and with groups.

Teach them how to cover missed lectures.

Give students tasks of duties

Discussion during the lecture.

3.3 ... ... ...

4.0 Communication, Information Technology, Numerical 4.1

The student should illustrate how to communicating with:

Peers, Lecturers and Community.

Creating

working groups with peers to collectively

Discussing group work sheets.

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NQF Learning Domains And Course Learning Outcomes

Methods prepare: solving

problems and search the internet for some topics.

4.2

The student should interpret how to Know the basic statistical principles using the internet.

Give the

students tasks to measure their:

mathematical skills,

computational analysis and problem solving.

Discuses with them the results of computations analysis and problem solutions.

4.3

The student should appraise how to Use the computer skills and library.

Encourage the student to ask for help if needed.

Give

homework's to know how the student

understands the numerical skills.

4.4

The student should illustrate how to Search the internet and using software programs to deal with problems.

Encourage the student to ask good question to help solve the problem.

Give them comments on some resulting numbers.

4.5 ... ... ...

5.0 Psychomotor

5.1

Not applicable Not applicable Not applicable

5.2

Not applicable Not applicable Not applicable

5.6 ... ... ...

5. Schedule of Assessment Tasks for Students During the Semester:

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Assessment task Week Due

Proportion of Total Assessment

1

^{Midterm 1} ⁵^th^week ^{15 %}

2

Midterm 2 10^th week 15%

3

Midterm 3 15^th week 15%

4

Homework + reports + Quizzes During the

semester

15%

5

Final exam End of

semester

40 %

6 ... ... ...

D. Student Academic Counseling and Support

1- 6-office hours per week in the lecturer schedule.

2- The contact with students by e-mail and website.

E. Learning Resources

1. List Required Textbooks :

 Probability & statistics for engineers & scientists. Ronald E. Walpole . . . [et al.]. Prentice Hall. 2012 — 9th ed. ISBN 978-0-321-62911-1

 Modern Mathematical Statistics with Applications. Jay L. Devore Springer New York Dordrecht Heidelberg London 2012 2^nd ed. ISBN 978-1-4614-0390-6



...

2. List Essential References Materials :

 Applied Statistics and Probability for Engineers. D.C. Montgomery & G. C. Runger.

John Wiley & Sons. 2003.

 Introductory Statistics. Wonnacott, T. H., and Wonnacott, R. J. John Wiley & Sons. 1969



...

3. List Recommended Textbooks and Reference Material :

 Probability & statistics for engineers & scientists. Ronald E. Walpole . . . [et al.]. Prentice Hall. 2012 — 9th ed. ISBN 978-0-321-62911-1

 Modern Mathematical Statistics with Applications. Jay L. Devore Springer New York Dordrecht Heidelberg London 2012 2^nd ed. ISBN 978-1-4614-0390-6

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 Applied Statistics and Probability for Engineers. D.C. Montgomery & G. C. Runger.

John Wiley & Sons. 2003.

4. List Electronic Materials :

.

http://ocw.mit.edu/courses/electrical engineering-and-computer-science/6-041sc-probabilistic- systems-analysis-and-applied-probability-fall-2013/unit-i/quiz-1/

 http://faculty.mu.edu.sa/m.alsaadani/MCQ

5. Other learning material :



... ...



...

.

F. Facilities Required

1. Accommodation

-Classroom with capacity of 30-students.

 - Library.

.

2. Computing resources



... ...

3. Other resources



...

G Course Evaluation and Improvement Processes

1 Strategies for Obtaining Student Feedback on Effectiveness of Teaching:

 Student evaluation electronically organized by the University.



...



...

2 Other Strategies for Evaluation of Teaching by the Program/Department Instructor :

 The colleagues who teach the same course discuss together to evaluate their teaching

...



...

3 Processes for Improvement of Teaching : .

.

- Course report, Program report and Program self-study.

 - A tutorial lecture must be added to this course



...

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4. Processes for Verifying Standards of Student Achievement

 The instructors of the course are checking together and put a unique process of evaluation.

...



...

5 Describe the planning arrangements for periodically reviewing course effectiveness and planning for improvement :

.

* Student evaluation.

* Course report.

* Program report.

* Program self-study.



... ...

Course Specification Approved

Department Official Meeting No ( ….. ) Date … / …. / ….. H

Course’s Coordinator

Department Head

Name : M.EL-Saadani Name :

...

Signature :

.. ...

Signature :

...

Date : …./ … / …… H Date : …./ … / …… H