ST101 : Introduction to statistics

Department

Department of Computer Science

Academic Program

Bachelor in computer science

Type

Compulsory

Credits

04

Prerequisite

Intended learning outcomes

§ To introduce Statistics and its importance to the students and to define the types of data and how to collect and summarize this data,

§ To study the measures of central tendency and dispersion and other concepts such as kurtosis and skewness.

§ Concept of simple linear correlation and simple linear regression and the relation with each other.

§ General concepts of probability.

Teaching and learning methods

· 1- Theoretical lectures

· 2- Practical lectures (exercises solving) using calculating tools.

Methods of assessments

a. Knowledge and understand

To provide student understand statistical knowledge with a very professional way by:

To introduce the student to some special data- terms which are widely used in statistics.

a1

To understand the descriptive analysis to the data by using the appropriate descriptive measures.

a2

To study the type and degree of correlation between two variables and their regression equation.

a3

To know the axioms of the theory of probability and how to find probabilities.

a4

b. Mental skills

To help student of having appropriate statistical skills:

to be able to classify data and to graphically represent it

b1

to be able to measures of central tendency and dispersion and other concepts such as kurtosis and skewness.

b2

to be able to detect the linear relation of two variables and to find the value of correlation and to explain it.

b3

to be able to obtain the sample space and calculate the probabilities.

b4

c. Practical & professional skills

After the completion of the course a student supposed to be able to:

To recognize types of data and how to present and summarize data.

c1

To select the appropriate measure of central tendency, dispersion, kurtosis and skewness.

c2

Determine the concept of correlation and its relation with regression.

c3

To use the numeration methods to calculate probabilities.

c4

d. Generic and transferable skills

Students to be able to work as a team and that to treat data sets.

d1

Students to be able to use calculators and other tools to analyze data.

d2

Students to be able to gain skills of describe and represent data.

d3

1. References

place

writer

Edition

Publisher

Reference Type

Class teacher notes

Course Notes

University selling store

العماري & العجيلي

2000

الاحصاء والاحتمالات النظرية والتطبيق

Text book

Peter Dalgaard

2nd

Introductory Statistics with R

Sub-Text book

Journals

Internet cites

others

2. The required capabilities to implement the course

Notes

Facilities to be offered

#

Computer lab with capacity of at least 30 students

1

Data show

2

Equipped class rooms

3