How do you keep your statistical skills and knowledge up to date and relevant?

In my experience, keeping statistical skills up to date involves regularly engaging in online courses and certifications through platforms like Coursera or edX. I focus on emerging topics such as data science, machine learning, and advanced analytics to stay informed about current methodologies. This structured learning approach helps me adapt to new trends and apply fresh techniques in my work. Additionally, I stay active in professional communities, joining forums or attending webinars where industry experts share insights. Practicing these skills on real-world projects reinforces my learning, ensuring my statistical knowledge remains relevant and practical.

Para manter minhas habilidades e conhecimentos atualizados e relevantes na área de Melhoria Contínua, priorizo constantemente a aprendizagem contínua e a pesquisa. Participar de cursos, workshops e conferências relacionadas à gest?o da qualidade e processos é fundamental. Além disso, fa?o uso frequente de ferramentas como Lean Six Sigma e métodos como PDCA (Plan, Do, Check, Act) para aprimorar minha prática. Mantenho-me informado sobre as últimas tendências e desenvolvimentos na indústria, lendo livros, artigos acadêmicos e publica??es relevantes. Também valorizo a troca de experiências com colegas da área, participando de grupos de discuss?o e fóruns online.

Statistical Process Control (SPC) is a quality management tool that employs a statistical methodology to monitor and control processes. Its goal is to ensure consistency and reliability in the production of goods or delivery of services. SPC involves collecting and analyzing data to identify variation within a process, distinguishing between common cause variations inherent in the system and special cause variations that indicate a specific issue. The key principles of SPC include the use of control charts, which graphically display process data over time. Control charts help distinguish between normal process variations and those that require intervention.

To keep your statistical skills and knowledge up to date, embrace a mindset of continuous learning and stay open to new methods and approaches. Regularly engage with industry literature, online courses, and professional communities to stay informed about the latest developments. Apply new techniques in your work to reinforce your learning and understand their practical applications. Attend workshops, webinars, and conferences to gain insights from experts and peers. Collaborate with colleagues on challenging projects to exchange knowledge and explore different perspectives. By consistently seeking out new learning opportunities and remaining adaptable, you ensure your skills stay relevant and effective in a rapidly evolving field.

Statistical Process Control is often a minimum requirement in regulated industries, identified through either Customer Specific Requirements, or within a businesses Quality Management system. Statistical Process Control provides the voice of the process on the controlled (measured) characteristic, and can indicate when to act depending on data patterns.

In a laboratory setting, SPC is an invaluable tool to control processes and methods for analytical techniques. We define controls at certain concentrations to be run in tandem with samples with LOD and LOQs defined as well. The recovery of a continuous calibration verification, or CCV standard relays important information about the viability of your instrument or method. This lends well, and is in compliance to ISO standards.

Statistical Process Control is often a component in Six Sigma training, from introduction to implementation, as it is data driven and utilises many statistical analyses. These are covered within LinkedIn learning for an easily accessible medium.

I have found the following ways to be helpful in keeping statistical skills up to date. -Ensure all my decisions are data driven -Refresher courses to keep skills up to date -Teach and mentor others

There is great opportunity to refine your SPC implementation during validation of problem solutions. Whether on a continuous plan, or a sample size basis, where measurements are taken you can apply SPC for a period to understand the process behaviours and further interrogate efficacy of solutions. A key lynchpin of SPC is understanding the inputs which relate to the data being recorded. With time or opportunity, it is advantageous to experiment with these inputs to a product (in a contained and controlled window) to understand if the SPC is providing valuable data.