Laboratory of Statistical and Computing Services offers training to a range of audiences from relatively inexperienced users of statistics through to experienced statisticians. If you, your staff or your colleagues need help with statistics or general help in dealing with data, we may be able to address your needs. With all our training activities, our aim is to impart the necessary skills to deal with your specific requirements. Our emphasis is always on the practical use of statistics. Below are the sevices that we provide:
Individual/Group Appointments Sometimes the needs of a client are so specific that rather than a formal training course, the most effective way to address their needs is more personalized consultancy. Appoinment will be set up upon request by a small group of people (between 1 and 4) by contacting our officers through e-mail or by phone call. Consultancy hours offer the opportunity to work on specific topics, or build skills with the help of an experienced statistician. Free consultancy will be given ONLY for staff and students internal to the Universiti Putra Malaysia. We encourage personal contact and are happy to discuss how to best address your needs.
Short Courses/Workshops For clients that are able to come to our purpose-built facilities at INSPEM, we offer an annual public program of over 12 courses. Some of these are aimed at scientists, researchers, technologists, decision makers and administrators, and are intended to improve the skills and understanding for those who need to use statistics. The short courses/workshops usually takes around two days to complete and normally will be organized together with a hands-on activities at Ulugh Berg Laboratory of INSPEM. The other short courses/workshops at a more advanced level, are aimed at applied statisticians and related professionals. For more information on courses, dates and prices follow the link to our short course program.
Below is the list of available topics for consultation:
Statistics: 1. Complex Data Mining 2. Handling Missing Data 3. Instrumentation and Measurement 4. Sampling Techniques 5. Regression Analysis 6. Survival / Reliability Analysis 7. Extreme Value Analysis 8. Robust Statistics 9. Structural Equation Modeling 10. Small Area Estimation 11. Bayesian Statistics 12. Multivariate Analysis 13. Time Series Analysis 14. Exploratory Data Analysis 15. Statistical Modelling
Statistical & Scientific Computing: 1. R 2. SPSS 3. SAS 4. Stata 5. Minitab 6. LaTeX 7. High Performance Computing 8. Parallel Programming / Computing 9. Python 10. MATLAB 11. C / C++