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أسئلة شائعة


A Course Identification and General Information

1.  Course title and code  Statistics and Probability 2   Stat 103

2.  Credit hours 4

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

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

College of Science students of mathematics, physics and biochemistry

4.  Name of faculty member responsible for the course Dr Hanan Aly, Dr Moshira Ismail and Mrs Raisa Medani  


5.  Level/year at which this course is offered 

6.  Pre-requisites for this course (if any)  none   Stat 101


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.

*Understanding the principles and skills of statistical inference and how to apply them on real data.

*Acquiring knowledge of how to choose a random sample and calculate related statistical measures.

 *Acquiring the ability of performing analysis of variance and analysis of regression.

*Acquiring numerical skills in computing through the application of statistical packages. 

*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)


The course is periodically reviewed by the instructors and the version of the statistical package used in the course is always updated.




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



No of




Review of what has been studied in 101







Sampling Distributions and the use of the central limit theorem






Tests of hypotheses and confidence intervals for one population







Tests of hypotheses and confidence intervals for comparing two populations 







Chisquare distribution applications in goodness of fit and testing homogeneity and independence                                                                                                           







Analysis of variance







Analysis of correlation and regression







Nonparametric tests




2 Course components (total contact hours per semester):                         


Credit hours: 60

Actual hours:45



Credit hours:15

Actual hours:30





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

*Knowledge of the central limit theorem

*Knowledge of the normal, t, F and X2 distributions and how to use their related tables


*Knowledge of how to make statistical inference from a sample


*.Knowledge of how to perform analysis of variance and regression analysis

*Knowledge of some nonparametric tests


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

*Lectures and tutorials.

*Participation of students through  discussions

*Solving homeworks which are 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 applying knowledge acquired in statistical inference to analyse real life situations.

Skills of interpreting results

Skills of using different parametric and nonparametric tests in appropriate situations



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

Lectures and tutorials where various examples are given

Applying the statistical package minitab

(iii)  Methods of assessment of students cognitive skills


Through  problems in exams and assignments which require critical thinking





c. Interpersonal Skills and Responsibility

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

*punctual attendance in lectures and tutorials is required

*students are required to hand out assignments at scheduled times



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

Giving regular assignments



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

Recording students attendance



d.   Communication, Information Technology and Numerical Skills

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

Skills in computing through using minitab


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

*students are given thorough training on how to apply minitab

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

practical exam using minitab package

*written exams contain  some questions which are solved using provided computer output


e.  Psychomotor Skills (if applicable)

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

Not applicable



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

Week due

Proportion of Final Assessment




First Midterm examination                                                                               








Second Midterm examination








Practical examination







Final exam

As scheduled by registrar   


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