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 T P O
28 23 8

L=lecture ; T=Tutorial; P=Practical; O=Others (Exam)

Total Guided and Independent Learning:

120
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 (LO1-C2: A2)
2.to compute and provide inferences for descriptive measures of statistical data (LO2: P3,A3)
3.to verbally communicate with peers and lecturer on the project assign (LO4-CS3: P3)
4.to participate in decision making by applying various statistical techniques (LO6-EM2: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. TEACHING-LEARNING AND ASSESSMENT STRATEGY Teaching-learning 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:
· Formative – tutorials, assignment and projects, quizzes, mid-semester exam and final semester exam
· Summative – in-class exercises, observation, participation and Q & A session

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
Component %
Continuous Assessment 50
Final examination 50
Total 100
16. CONTENT OUTLINE OF THE COURSE/MODULE AND SLT PER TOPIC
Topic Lecture Tutorial Test/Quiz/Exam Assignment Assessment(Library Search) Self-study Total
Introduction 2 1 3 6
Presentation of Information/data 2 1 3 6
Descriptive Measures for Numerical Data 4 2 6 12
Basic Probability Theory 2 3 3 8
Various Continuous Distributions 4 3 6 13
The Normal Distributions 4 2 6 12
Confidence Interval 4 2 6 12
Hypothesis Testing 4 3 6 13
Simple Linear Regression 2 3 3 8
Continuous Test/Quiz/Assessment 5 10 15
FINAL 3 9 12
TOTAL 28 23 8 0 19 42 120
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
2.Douglas Downing and Jeffrey Clark. 2010. Business Statistics. Barron’s Educational Series.
3.McClave James T., P. George Benson & Terry Sincich. 2008. Statistics for Business and Economics, Prentice Hall Inc: New Jersey.
4.Lind, Douglas A., William G. Marchal and Samuel A. Wathen. 2000. Basic Statistics for Business & Economics, Sixth Edition. McGraw Hill. Boston U.S.A.
5.Groebner, David F., Patrick W. Shannon, Phillip C. Fry and Kent D. Smith. 2008 Business Statistics: A Decision-Making Approach. Seventh 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 cross-tabulation 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 hypothesis-testing 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%)