We chose our company name, Creascience to emphasize that creativity can mix efficiently with science. In this blog, we share illustrations of how a correct use of statistics leads to drastic improvements of scientific research. Come back often to read our latest findings or simply follow this link to get notified by email (guaranteed 100% ad-free).
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The Need for Design of Experiments (DoE) in Medical Device Development Phases
The role of DoE in the development of medical devices is extremely important. It is an essential strategy for optimizing the design, manufacturing, and performance of these devices. It is a systematic approach used to determine the relationship between factors affecting a process and the output of that process. By using the design of experiments…
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What is Statistical Thinking?
Statistical thinking is an approach to problem-solving that involves understanding and applying concepts from statistics to make informed decisions and draw conclusions. It’s not just about crunching numbers, but about thinking critically and systematically to understand variability, patterns, and relationships in data. 🎯 It helps structure and consolidate research activities so that they are reproducible,…
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Understanding Sources of Variation – The Key to Meaningful Results
To draw general conclusions about a population, it is necessary to sample its variation. Introduction Variability in experiments is inevitable due to biological and technical effects. Controlling technical variability enhances internal validity, while maintaining biological variability allows generalization to the population. Experimental control, randomization, blocking, and replication help. This paper delves into the impact of…
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Strategic Thinking in Biotech/Medtech R&D
During the COVID-19 pandemic, life sciences investment surged, with biotech stock valuations and IPO funding peaking in 2021. However, investment has declined significantly, leading to tightening R&D belts and streamlined project pipelines to retain financial headroom for key programs. The Need for Thinking Differently Life science venture capital has remained above pre-pandemic levels due to…
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Study Design: Think “Scientific Value” not “P-Values”
“Statistically based experimental designs have been available for over a century. However, many preclinical researchers are completely unaware of these methods, and the success of experiments is usually equated only with ‘p < 0.05’. By contrast, a well-thought-out experimental design strategy provides data with evidentiary and scientific value. A value-based strategy requires implementation of statistical design principles…
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Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors
“Statistical power analysis provides the conventional approach to assess error rates when designing a research study. However, power analysis is flawed in that a narrow emphasis on statistical significance is placed as the primary focus of study design. In noisy, small-sample settings, statistically significant results can often be misleading. To help researchers address this problem…