You are invited to join the IASC African Members Group Webinar:
Statistical Quality Control with Applications in R
Statistical quality control (SQC) has three main keywords: Statistics, Quality, and Control. Therefore, SQC concept and practice are the coalescences of the three words. In simple terms, SQC is the use of statistical techniques to monitor/control the quality of a process, product, or service. Statistical process control (SPC) tools are often used to monitor a process, while monitoring a product has to do with the acceptance sampling scheme (ASS). Thus, one can conveniently say that the two major branches of SQC are the statistical process control (SPC) and the acceptance sampling scheme (ASS). In SPC, the control chart is the principal tool used to monitor a process’s stability and capability.
The control chart is a critical technique in SPC to monitor a process. In general, control charts are applied in two different stages: Phase I control and Phase II monitoring. In Phase I control, historical data of the process are collected and analysed to understand the variation of the process over time, evaluate the process stability and estimate the in-control process parameters. In Phase II monitoring, the process is monitored in real-time to quickly detect changes in process parameters.
The main reason for monitoring a process is to determine the type of variation that drives such a process. If a process is driven by chance variation, then the process will behave normally, and thus random force will be in operation. We say such a process is in statistical control. The random force is the same force that is said to be in operation in life sciences experiments. An assignable variation is at work if there is a distortion in the process’s normal behaviour. When such happens, we say that the process is no longer stable and operates in out-of-control (OOC) conditions. When there is an out-of-control signal, subject experts are allowed to interpret such signal.
Over the year, SQC has become a versatile tool in the study of variation in different areas of research and policymakers. Such areas are engineering, medicine & allied medical sciences, life & wet sciences, behavioural sciences, manufacturing and service organisations, sports, the legal profession, humanities, and so on. I read an article recently by a “supposed expert” who applied the control chart concept to hospital data. The results were incredible, but the interpretation of the results was distorted simply because the author was not well grounded in the concept of variation in SQC and its interpretation. Thus, in this webinar, we shall be discussing basically the concept and application of the most globally used SQC tool. The Control Chart! While hands-on will be on R.
Prof. Kayode S. ADEKEYE
Kayode Samuel Adekeye is a Professor of Statistics, the pioneer Deputy Vice-Chancellor, and Director of Academic Planning and Quality Assurance at Redeemer’s University, Ede, Nigeria. He is an erudite scholar and a teacher per excellence. He has supervised scores of students for the award of National Diploma, Higher National Diploma, BSc, MSc, and PhD in Statistics in five higher education institutions in Nigeria. He was a visiting Professor of Statistics at the University of Lagos from 2019 to 2020, and a visiting Professor of Statistics and Director of Planning and Quality Assurance at the University of The Gambia in 2021.
Prof. Adekeye has facilitated several training workshops on Quality Assurance in Higher Education management; such as DIES National Multiplication Trainings (NMT) workshop 2019-2020 for Higher Education Institutions in Anglophone West African countries; Training on Internal Quality Assurance in Southeast Asia 2020-2021; Training on Internal Quality Assurance in the SADC region 2020-2021; AfriQAN Workshop on quality assurance for higher education leadership; and the HAQAA2 Training Course on Internal Quality Assurance: IQA-4-Africa – From Pan-African Policy to Practice.
Professor Kay is happily married, and the marriage is blessed with lovely children.
Timothy A. OGUNLEYE
Presently, Timothy A. OGUNLEYE holds two degrees in Statistics: Master of Science (M.Sc.) and Bachelor of Science (B.Sc. – Hons.) from one of the prestigious universities in Nigeria – University of Ilorin. This is in addition to Ordinary National Diploma and Higher National Diploma in Statistics obtained from the Federal Polytechnic, Ede, Osun State, Nigeria. He has more than 15 years of work experiences that cut across both industries and academia. Timothy has worked for a number of local and international organizations including UNDP, NAPTIP, NAICOM, LBS, to mention but a few. He’s also an experienced academic university staff. Currently, he’s a lecturer at the Department of Statistics, Osun State University, Osogbo, Nigeria. He is acting as the Secretary-General, International Association for Statistical Computing - African Members Group. His research areas includes modelling and econometrics, computational statistics, morphometrics and biostatistics.