IASC African Members Group presents:
Webinar on Response Surface Methodology with Application in R
Response surface methodology (RSM) is a collection of statistical and mathematical techniques useful for developing, improving, and optimizing processes. It also has important applications in the design, development, and formulation of new products, as well as in the improvement of existing product designs. The most extensive applications of RSM are in the industrial world, particularly in situations where several input variables potentially influence some performance measure or quality characteristic of the product or process. This performance measure or quality characteristic is called the response. It is typically measured on a continuous scale, although attribute responses, ranks, and sensory responses are not unusual. The RSM package for R provides several functions to facilitate classical response surface methods. The package is used to generate response surface designs, fit first and second order response surface models, make surface plots, obtain the path of steepest ascent, and do canonical analysis. The webinar will focus on generating an appropriate response surface design in R as well as using the software for fitting and displaying response surface models. It is envisaged that by the end of the webinar participants will have the requisite skills to undertake RSM analysis in R.
Speaker: Dr. Ayubu Anapapa Okango
Dr. Ayubu Anapapa Okango is a Senior Lecturer of Statistics in the Department of Mathematics and Actuarial Science, Murang’a University of Technology. He holds a PhD in Biostatistics of Moi University, a Master of Science degree in Statistics of Kenyatta University, a Postgraduate Diploma in Information Technology Management of the University of Sunderland and a BSc. Majoring in Statistics and Computer Science (First class honors) from Jomo Kenyatta University of Agriculture and Technology.
Dr. Anapapa has over 20 years’ experience in lecturing at university and tertiary level having previously worked at Jomo Kenyatta University of Agriculture and Technology, Government Training Institute and University of Eldoret. He has also worked as Data Manager with Kenya Medical Research Institute and as a Biometrician with Kenya Medical Research Institute.
His area of specialization is in biostatistics, statistical computing, design of experiments and statistical modelling.
Dr. Anapapa has successfully supervised 1 PhD student and 7 MSc students. He has published over 20 articles in peer-reviewed journals as well as presented in a number of scholarly conferences.