course presentations

King Saud University
College of Business Administration
Quantitative Analysis Department (QUA)
Course's Professor: Dr. Fuad AlAwwad
Office: S227 Email: [e-mail], Twitter: @fawwwad
Course Specifications

A- Basic Information
Code: QUA 107	Course Title:  INTRODUCTION TO STATISTICS IN BUSINESS
Section:	Programme: Undergraduate
Pre-requisites: None	Credits Hours: Theoretical           3                            Practical               1
Target Students: This course is designed for college of business                                   administration's students as an introduction to statistics.
Department offering the course: Quantitative Analysis Department (QUA)
B- Professional Information
Provide students with the concepts and special skills for collecting, classifying, analyzing and presenting the data		1- Overall aims of course
- Collecting, tabulating and presenting of data. - Measures of central tendency. - Measures of dispersion - Index numbers. - Principles of probability. - Probability Distributions		2- Course brief Contents
- lectures - exercises - cases studies - Group discussions		3- Teaching and Learning     Methods
4- Students Assessments
- Medterm Exam - Weekly Homework - Final exam		4/1- Tools
-First Exam: 29/5/1437 (9/3/2016) -Unified Exam: TBA Replacement Exam: TBA You are required to attend the Unified exam. If you miss the unified exam and you have a valid excuse you will be allowed to enter the replacement exam otherwise you will miss the 30 points.		4/2- Time Schedule
- First Exam: 20 Marks - Unified Exam: 30 Marks - Weekly attendance and participation: 10 Marks - Final exam:     40 Marks
5- List of references
By lectures		5/1- Text notes
Text Book: Statistical Techniques in Business and Economics (2010) By Douglas A. Lind, William G. Marchal, and Samuel A. Wathen.		5/2- Text books

 

 
Detail contents

Chapter	Title	Required Topic
1	What is Statistics	Introduction - What is Meant by Statistics? -  Types of Statistics - Population versus Sample - Types of Variables - Levels of Measurement.
2	Describing Data: Frequency Distributions and Graphic Presentation.	Introduction - Constructing a Frequency Table  - Constructing a Frequency distributions - Relative Frequency Distribution - Histograms  -Frequency polygons - Cumulative frequency distributions - Software applications (by Excel).
3	Describing Data:  Numerical Measures	Introduction - Population Mean - Sample Mean – Properties  of the Arithmetic Mean – The Weighted Mean- The Median - Properties of the Median -  The Mode - The Relative Positions of the Mean, Median and Mode – The Geometric Mean –Why Study Dispersion - Measures of Dispersion - Range -Mean Deviation  - Variance and Standard Deviation - Chebyshev’s Theorem – The empirical Rule - The Arithmetic Mean of Grouped Data - Variance  and Standard Deviation for  Grouped Data – Software applications (by Excel).
4	Describing Data: Displaying and Exploring Data	Introduction – Dot Plots - Stem and Leaf – Quartiles, Deciles and Percentiles - Box plots - Scatter plot. Software applications (by Excel).
5	A Survey of Probability Concepts	Introduction – What is a Probability – Approaches to Assigning Probabilities - Classical Probability - Mutually Exclusive Events - Collectively Exhaustive Events - Rules for Computing Probabilities –Rules of addition – Rules of Multiplication -  Conditional Probability - Contingency Tables -  Tree Diagrams - Bayes’ Theorem
6	Discrete Probability Distributions	Probability Distribution - Characteristics of a Probability Distribution - Random Variables - The Mean of a Probability Distribution - The Variance, and Standard Deviation of a Probability Distribution - Binomial Probability Distribution - Poisson Probability Distribution – Hypergeometric Probability Distribution.
7	Continuous Probability Distributions	Uniform Probability Distribution-   Characteristics of a Normal Probability Distribution - The Normal Probability Distribution – The Normal Approximation to the Binomial - Software applications (by Excel).
15	Index Numbers	Unweighted Indexes - Weighted Indexes (Lespeyres, Paasche and Fisher’s Ideal Index) - Value Index