1.  NAME OF COURSE / MODULE  BUSINESS STATISTICS  
2.  COURSE CODE  MDB2013  
3.  NAME(S) OF ACADEMIC STAFF  
4.  RATIONALE FOR THE INCLUSION OF THE COURSE/MODULE IN THE PROGRAMME  This course is a foundation of knowledge of basic application statistics in business. In addition, this course provides a platform on the relevancy of statistics in business decision.  
5.  SEMESTER & YEAR OFFERED  Semester 4 / Year 2 & Semester 5 / Year 3  
6.  TOTAL STUDENT LEARNING TIME (SLT)  Face to face:
L=lecture ; T=Tutorial; P=Practical; O=Others (Exam) 
Total Guided and Independent Learning:


7.  CREDIT VALUE  120/40 = 3.00 (3 credit); 2+2  
8.  PREREQUISITE (IF ANY)  NIL  
9.  OBJECTIVES  1.To familiarize students with concepts involve in statistical information, probability theory,
2.various statistical, distributions, sampling technique, confidence interval and hypothesis testing 3.To guide students to compute, perform data analysis and provide inferences for descriptive measures of statistical data. 4.To encourage students to participate in decision making by applying various statistical techniques. 

10.  LEARNING OUTCOMES  After completing this course, the students should be able:
1.to explain statistical information, probability theory, various statistical, distributions, sampling technique, confidence interval and hypothesis testing (LO1C2: A2) 

11.  TRANSFERABLE SKILLS  Student should be able to develop a good understanding of background in business statistics through a process of lectures, tutorial and group assignment.  
12.  TEACHINGLEARNING AND ASSESSMENT STRATEGY  Teachinglearning strategy:
· The course will be taught through a combination of formal lectures, exercise, group work, using authentic materials, informal activities and various textbooks. Collaborative teamwork will be fosters throughout the course. The use of examination and internal reporting assessment will assess the student’s ability to apply theoretical concept in context. Assessment strategy: 

13.  SYNOPSIS  The aim of this course is to provide a frame of reference for business major students on the importance of the statistics discipline in helping businesses make decisions or formulate strategies. The relevance of knowledge in statistics in accounting, finance, information systems, management and marketing is exposed. This course therefore focuses on the application of the various topics of statistics in businesses in their normal operation. This includes presentation of data, interpretation of results, presentation and evaluation of assumptions and strategies to adopt to overcome problems when assumptions are violated.
The integration of statistical software decrease the need for manual computation and students can devote more time on the interpretation of results. Students are however encouraged to master manual calculations in order to appreciate the statistical concepts. Students are expected to be able to recognize the statistical approaches to adopt when presented with statistical data. Therefore they are expected be able to recognize the business problems, formulate hypothesis and determine test methods and statistics involved and provide sound business interpretations in order to be able to impart advice based on the presented data 

14.  MODE OF DELIVERY  Lectures and tutorial (SCL)  
15.  ASSESSMENT METHODS AND TYPES 


16.  CONTENT OUTLINE OF THE COURSE/MODULE AND SLT PER TOPIC 


17.  REFERENCES:  Main reference:
1.Lind, Douglas A., Marchal, William G., and Wathen, Samuel A. 2013. Statistical Techniques in Business & Economics, Fifteenth Edition. McGraw Hill. Boston U.S.A. Additional references: 1.Brenson Mark, L., David M. Levine and Timothy C. Krehbiel 2009. Basic Business Statistics: Concepts and Applications 11th edition, Pearson Education, Inc., New Jersey 
Mapping of the course/module to the Programme Learning Outcomes
TOPIC 
Contact hours (week) 
Lesson Learning Outcome (Students are able to..) 
CLO  KI  Teaching & Learning Activities  Assessment Tasks 
Introduction  3  1.Explain the application of statistics in business and it sources in business.
2.Describe types of data used in business. 
LO1
LO4 
C2
CS3 
o Lecture  Feedback on the activity. 
Presentation of information/data 
3 
1.Explain the importance of organizing numerical data in tables, charts and graphs.
2.Discuss ethics in information presentation 3.Give an overview of using crosstabulation techniques 
LO4
LO6 
CS3
EM1 
o Lecture
o Tutorial activity 
Feedback on the tutorial activity. 
Descriptive Measures for Numerical Data  3  1.Describe the properties of central tendency, variation and shape in numerical data.
2.Calculate the descriptive summary measures from frequency distribution and for a population. 3.Construct and interpret a boxplot. 4.Describe the covariance and the coefficient of correlation. 
LO2
LO4 
P2
CS3 
o Lecture
o Tutorial activity 
Feedback on the tutorial activity. 
Basic Probability Theory  6  1. Understand the basic and conditional probability concepts.
2.Use Bayes’ theorem to revise probabilities. 
LO1  C2  o Lecture
o Tutorial activity 
Quiz 1 (15%) 
Various Continuous Distributions  5  1.Compute probabilities from the normal distribution. 2.To use the normal probability plot to determine whether a set of data is approximately normally distributed. 3.Compute probabilities from the uniform and exponential distribution. 
LO2  P2  o Lecture
o Tutorial activity 
Feedback on the tutorial activity 
The Normal distribution  7  1.To compute probabilities from normal distribution. 2.To use the normal probability plot to determine whether a set of data is approximately normally distributed 3.To compute probabilities from uniform, exponential and normal distribution. 
LO1
LO2 
C2
P3 
o Lecture
o Tutorial activity 
Feedback on the tutorial activity. 
Confidence Interval Estimation  6  1.Construct and interpret confidence interval estimates for the mean and the proportion.2.Determine the sample size necessary to develop a confidence interval for the mean or proportion  LO2  P2  o Lecture
o Tutorial activity 
Quiz 2 (15%) 
Hypothesis Testing  7  1.Explain the basic principles of hypothesis testing. 2.Use hypothesis testing to test a mean or proportion. 3.Evaluate each hypothesistesting procedure and the consequences if they are seriously violated. 4.Aware of ethical issues involved in hypothesis testing. 
LO1
LO2 LO6 
C2
EM3 
o Lecture
o Tutorial activity 
Feedback on the tutorial activity 
Simple linear regression  5  1.Use regression analysis to predict the value of a dependent variables based on an dependent variable/s. 2.Interpret regression coefficients 3.Determine which independent variables are most important in predicting a dependent variable/s. 
LO2  C2  o Lecture
o Tutorial activity 
Feedback on the tutorial activity.
Presentation and report (15%) 