1. 3 Days Workshop on 14 th – 16 th April 2015 Al-Khawarizmi Seminar Room and Al-Khaitam Laboratory, Mathematics Building Universiti Putra Malaysia 43400 UPM Serdang, Selangor. Organised by: Faculty of Science Universiti Putra Malaysia Resource Person: 1. Prof. Dr. Habshah Midi (Speaker) (Deputy Dean, Faculty of Science and Lecturer Dept. of Mathematics, UPM) 2. Dr. Anwar Fitrianto and Dr Sohel Rana (Facilitator) – Lecturer,Dept. of Mathematics, UPM) Her research interests focus on robust statistics, regressions, experimental designs, quality control, sampling techniques, bootstrapping techniques and application of statistical methods to real life problems. Dr. Habshah Midi has taught a wide variety of post-graduates and undergraduate courses such as design and analysis of experiments, regression analysis, robust statistics, mathematical statistics, quality control techniques, etc. Her student’s teaching evaluation marks has always been greater than 90%, which credits her the “Excellence in Teaching ” from the Faculty of Science, every year since it was introduced in 2002. In 2007, Dr. Habshah Midi was awarded the Fellowship Naib Canselor ( Excellence in Teaching ) and in 2010, she was nominated by UPM for the National Academic Award (Excellence in Teaching). Dr. Anwar and Dr Sohel Rana received their PhD degrees (Statistics) in 2010, under the supervision of Prof Dr. Habshah Midi. Professor Dr. Habshah Midi completed her Bachelors Degree in Mathematics from Drew University, USA. She received the Master of Applied Statistics from The Ohio State University, USA. In October 1981, she joined Universiti Putra Malaysia as a lecturer and pursued her PhD (Statistics) from Universiti Kebangsaan Malaysia where she was awarded her doctorate in 1995. Currently she is the Vice-President of Malaysia Institute of Statistics. Name: Title: Address: Telephone (hp): (Office): Email: Signature Date Fees : RM500.00 Student: RM350.00 Number of participants are limited to 40 Payments can be made either by cash,bank draft, cheque, LO payable to BENDAHARI UPM. – Please provide proof of payment) PLEASE REGISTER BY FILLING OUT THE REGISTRATION FORM AND MAIL OR FAX TO 03-89432508 OR ONLINE REGISTRATION AT http://math.upm.edu.my/daeworkshop For further information please contact: Mrs. Yeow Swee Lin Phone : 03-8946 6606, Fax: 8943 2508 Email: pauline@upm.edu.my REGISTRATION FORM

2. interpretation of the outputs obtained. After attending this course, the participants Should be able to plan, design and conduct experiments effectively and also be able to select an appropriate design. Participants will also have the opportunity to obtain statistical consulting service/statistical advice on the last day of the workshop. experimental situation, analysis of variance on the data collected, diagnostic and adequacy checking on the estimated design model, the estimation of and inference on the parameters of the model. WORKSHOP PROGRAM Day 1: 26 th July2011 8.00-8.30: Registration 8.30-8.40: Officiation by the Dean of Faculty of Science 8.40-10.15: Introduction to the basic principles of DOE and Analysis of Variance 10.15-10.45: Break 10.45-12.00: The Completely Randomized Design 12.00-1.00: Introduction to SPSS: Basic descriptive procedures 1.00-2.15: Lunch 2.15-3.30 : Randomized Complete Block and Latin Squares Design 3.30-4.30: Analysis of Variance using SPSS And output interpretation 8.30-10.00 Diagnostics and Adequacy checks. Multiple Comparisons 10.00-10.20Tea break 10.20-12.00 Factorial Design Multiple comparisons 12.00-1.00 Diagnostics and multiple comparisons using SPSS 1.00-2.30Lunch 2.30--4.30 Repeated Measure Design Discussion and output interpretation. 8.30-10.00 Repeated on One Factor Repeated on both Factor 10.00-10.30Tea Break 10.30-11.30Split Plot Design 11.30-1.00 Analysis of Variance using SPSS. 1.00-2.30Lunch 2.30-4.30 Analysis of Factorial Experiment Using SPSS/CONSULTATION HOURS 4.30-4.40Closing Ceremony DAY 3: 16 TH APRIL 2015 DAY 2: 15 th APRIL 2015 DAY 1:14 TH APRIL 2015 By ignoring the correct design and adequacy checking will lead to invalid inferences and inaccurate predictions. In this workshop participants will be introduced to the planning and analysis of appropriate statistically designed experiments in order to achieve the objectives of their research. Participants will have the opportunity to interactively use SPSS and will be guided on the Who Should Attend: Academicians, Researchers, Graduate Students and Researchers from various industries both public and private. 3 DAYS WORKSHOP ON THE RIGHT WAY TO DESIGN AND ANALYSE EXPERIMENTS Much of the research in engineering, social science and industry are empirical and makes extensive use of experimentation. Since statistical methods are used frequently to help policy makers in making decisions, it’s very vital for the researchers to have basic understanding of statistics. Because of the easy availability of the statistical packages such as SAS, SPSS, MINTAB etc, researchers who have a little knowledge in statistics have a greater scope to abuse statistics while analyzing their data. Without adequate knowledge in statistical techniques such as design and analysis of experiments, researchers simply instruct the packages to analyse data using their convenient design. Unfortunately, some researchers believe that knowing statistical packages is equivalent to knowing correct statistical techniques. They often are not aware of the fact that statistical packages just follow the instructions given to them and produce results accordingly. The packages do not know whether researchers have chosen the correct statistical techniques for their studies. Consequently, meaningless and misleading conclusions are obtained from an incorrect analysis. The correct choice of design is very important to ensure that appropriate data can be analyze by relevant statistical techniques which will produce results leading to valid and objective conclusions. Topics in a Design and Analysis of Experiments (DOE) course range from the introduction of the basic principles of DOE to recognizing the appropriate designs suitable for each