COURSE DESCRIPTION AND OBJECTIVES
The course will cover inferential statistics, regression modelling and forecasting techniques. It was designed to business school students who have taken an introductory statistics course. In the laboratory component, which is part of the course, you will learn to use Microsoft Excel and a particular statistical add-in package to perform analysis of data. The emphasis is on business applications rather than rigorous mathematics.

After completing this course students are expected to be able to:
(1) Understand statistics as a tool for data analysis.
(2) Apply regression analysis to business data using a simple statistical software (Microsoft Excel).
(3) Understand and interpret the result of regression analysis.
(4) Use several forecasting techniques to predict demand.

TEXTBOOK
PRIMARY TEXT

Lind, Douglas, William Marchal and Samuel Wathen. Statistical Techniques in Business and Economics, 14th Edition. Mc Graw Hill. 2010. [LIND]
ADDITIONAL TEXT
Pardoe, Iain.  Applied Regression Modelling, A Business Approach.  John Wiley & Sons, 2006 [PAR]
GRADING POLICY
Midterm Exam                         35%
Final Exam                                35%
Assignments/Quizzes              15%
Class participation                     15%

OTHER IMPORTANT INFORMATION
It is extremely important to keep up in this class. The course moves very quickly. Students should attempt as many of the problems (exercises) at the end of each chapter as possible. At least one problem representative of each topic covered in the course should be attempted. Suggested problems would include those for which solutions are available in the back of your textbook. Problem formulation and solving are an important aspect of learning statistics. If you are having trouble with any of the topics, talk to the tutors or the faculty immediately.

COURSE OUTLINE
(1) Introduction to Course Foundation: Interval Estimation
(2) Foundation: Hypothesis Testing
(3) Simple Linear Regression
(4) Multiple Linear Regression
(5) Multiple Linear Regression
(6) Index Numbers
(7) Forecasting Techniques
(8) Nonparametric Methods: Chi-Square Applications
(9) Statistics for Quality Control
(10) Case Study & Exercise

CLASS
(1) Business F – Thursday 08.00-10.30 – Room  106 business statistics november 30 class F
(2) Business B – Thursdya 13.00-15.30 – Room 102 business statistics november 30 class B

Assigment I 15 September 2011 – Class B – Exercise Chapter 13  no 49, 50,51,  “Statistical Technique in Business and Economics., Lind/Marchal/Weathen., McGraw Hill homework 1 B20113B – 21 September 2011

Assigmnet I 15 September 2011 – Class F – Exercise Chapter 13 no 40,41, 44 ” Statistical Technique in Business and Economics., Lind/Marchal.Weathen., Mc Graw Hill homework-1-b20113f-21-september-2011

Assigment II 5 Oktober 2011 – Class B and Class F – Chapter 14 no 17, 18, 19 ” Statistical Technique in Business and Economics., Lind/Marchal/Weathen., Mc Graw Hill homework 2 stat bisnis

Assigment Forecasting – Trend regression November 2th, 2011 – Class B and Class F – Chapter 16 no 22,23,24,25 ” Statistical Technique in Business and Economics., Lind/Marchal/Weathen., Mc Graw Hill  The Answer Of forecasting Exercis1

Assigment Forecasting – Seasonal  November 9th, 2011 – Class B and Class F – Chapter 16 no 26,27,28,29, 30 ” Statistical Technique in Business and Economics., Lind/Marchal/Weathen., Mc Graw Hill The Answer Of forecasting Exercise seasonal

Assigment Non-Parametric Methods November 23th, 2011 – Class B and Class F – Chapter 18 no 4, 12, 14, 16,18 ” Statistical Technique in Business and Economics., Lind/Marchal/Weathen., Mc Graw Hill The Assisgment of Non Parametric Methods

Midterm Examination October 24 th – Soal UTS BusinessStat v1_QA_2011_simple answer key
Group Discussion “Multiple Regression 5 Oktober 2011