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The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Course Title: Introduction to Statistics
Course Code: BADM 103
I. Basic Course Information
Program(s) on which the course is given: Business Administration
Core or Elective element of program Core course:
Department offering the course: Business
Academic level: First
Semester in which course is offered: Fall Semester
Course pre-requisite(s): none
Credit Hours:3.00
Contact Hours Through:
Lecture
3.0
Tutorial*
2.0
Practical*
0.0
Total
5.0
Approval date of course specification: September 2013
II. Overall Aims of Course
This course provides an insight of the basic techniques of descriptive statistics insight
of basic concepts and definitions as well as the typology of data sources and
classification. It also developes an understanding of the data listing techniques,
grouping and data description through measures of location and variation. The course
focuses on the following topics: Probability concepts and probability distributions.
III. Program ILOs covered by course
Program Intended Learning Outcomes (By Code)
Knowledge &
Intellectual Skills
Professional Skills
Understanding
K2,K10
I1,I4,I6
P4, P6,P9
General
Skills
G5
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The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
IV. Intended Learning Outcomes of Course (ILOs)
a. Knowledge and Understanding
Upon Completion of the course, students should be able to:
K.1 Distinguish between key definitions: population vs. sample, primary vs.
secondary data types, qualitative vs. quantitative data, and time series vs. crosssectional data
K.2 State the difference between descriptive and inferential statistics
K.3 State the differences and similarities between different sampling methods
K.4 Discuss how to categorize data by type and level of measurement
K.5 Distinguish between different techniques for describing and displaying data
numerically and graphically
K.6 Distinguish between different statistical measures: central tendency, dispersion,
location, and others
K.7 Discuss different approaches to assessing probabilities
b. Intellectual/Cognitive Skills
Upon Completion of the course, students should be able to:
I.1 Interpret data presented in frequency distributions or graphically
I.2 Compute and interpret different central tendency measures, dispersion measures,
measures of location, and other measures such as the coefficient of variation, and
skewness
I.3 Use numerical measures along with graphs, charts, and tables to describe data
I.4 Apply common rules of probability
c. Practical/Professional Skills
Upon Completion of the course, students should be able to:
P.1 Construct and interpret tabular and graphical data representations: frequency
distribution, histogram, bar charts, pie charts, line charts, scatter diagrams, and
stem-and-leaf diagrams
P.2 Apply different statistical measures to real-life problems
P.3 Construct and interpret a box and whisker graph
P.4 Apply probability to business decision-making situations
d. General and Transferable Skills
Upon Completion of the course, students should be able to:
G.1 Demonstrate necessary skills in time management, organization practices.
G.2 Identify, and present the numerical dimensions of a problem
G.3 Demonstrate problem solving skills
2
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
V. Course Matrix Contents
1-
Course ILOs Covered by Topic
(By ILO Code)
K&U
I.S.
P.S.
G.S.
Main Topics / Chapters
Duration
(Weeks)
The (Where, Why, and How
of ) Data Collection
1
K1,K2,K3
K4
I3
P2
3
K5
I1,I3
P1,P2
5
K5, K6
I1,I2
P2,P3
3
K7
I4
P2,P4
Graphs, Charts, and Tables–
Describing Your Data
Describing Data Using
3Numerical Measures
Using Probability and
4Probability Distributions
Net Teaching Weeks
2-
G1-G2G3
G1-G2G3
G1-G2G3
G1-G2G3
12
VI. Course Weekly Detailed Topics / hours / ILOs
Week
No.
1
2
3
4
5
6
7
8
9
10
Sub-Topics
Total
Hours
What is statistics?
Tools for collecting data/
3
Populations, samples, and sampling
Data types & measurement level
5
Describing Data (Graphically & Tables)
Frequency distributions & histograms
5
Describing Data (Graphically & Tables)
Bar charts, pie charts, & stem leaf
5
Line charts & scatter diagrams
Describing Data (Numerically)
Central Tendency Measures (Mean,
5
Mode)
Describing Data (Numerically)
Central Tendency Measures (Median,
5
Weighted Mean)
Midterm Exam
Describing Data (Numerically)
Dispersion Measures (Range and Mean
5
Deviation )
Describing Data (Numerically)
Dispersion Measures (Variance and
5
Standard Deviation)
Describing Data (Numerically)
Location Measures (Percentiles,
Quartiles), Interquartile range, Box and
5
whisker plot
Other Measures (Skewness and
coefficient of variation)
Contact Hours
Theoretical
Practical
Hours
Hours*
3
3
2
3
2
3
2
3
2
3
2
3
2
3
2
3
2
3
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
11
12
13
14
15
Probability
Basics of Probabilities (Events & sample
5
space, tree diagrams, mutually exclusive)
Methods of Assigning Probability
Probability
Probability Rules (Addition rule,
5
Complement rule)
Conditional Probability
5
Revision
5
Final Exam
Total Teaching Hours
63
3
2
3
2
3
3
2
2
Teaching/Learning
Method
Lectures & Seminars
Tutorials
Computer lab Sessions
Practical lab Work
Reading Materials
Web-site Searches
Research & Reporting
Problem Solving /
Problem-based Learning
Projects
Independent Work
Group Work
Case Studies
Presentations
Simulation Analysis
Selected
Method
VII. Teaching and Learning Methods


Course ILOs Covered by Method (By ILO Code)
K&U
All
All
Intellectual
Skills
All
All
Professional
Skills
All
All
General
Skills
All
All
Others (Specify):
4
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Selected
Method
VIII. Assessment Methods, Schedule and Grade Distribution
Course ILOs Covered by Method
(By ILO Code)
Assessment
Method
K&U
I.S.
P.S.
Midterm
Exam
Final Exam
Quizzes
Course
Work
Report
Writing
Case Study
Analysis
Oral
Presentations
Practical
Group
Project
Individual
Project
Others
(Specify):
G.S.
Assessment
Week
Weight /
No.
Percentage

K1,K2,K3,K4,K5 K6
I1,I2,I3
P1,P2,P3
All
20%
7


All
K1,K2,K3,K4,K5,K6
All
I1,I2,I3
All
P1,P2,P3
All
All
50%
10%

All
All
All
All
20%
15
5,11
All
Term
IX. List of References
Required Text Books
David F. Groebner, P. W. Business Statistics a Decision-Making
Approach: Mathxl. Pearson College Division, 2010.

Course notes

Recommended books

Title: Probability and Mathematical Statistics
Author: Shelden M.Ross, Edition: First Edition (Academic
Press)
Title: Statistical Thinking for Managers
Author: Hildebrand/Ott , Edition: Fourth Edition
Periodicals, Web sites, 
etc …
X. Facilities required for teaching and learning
 Teaching aids
 Computer aided data show
 White boards
Course coordinator: Dr. Ihab el Khodary
Head of Department: Dr. Dina Krema
Date: September 2013
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