In parts 1 & 2 of our series on the confidence interval, we have covered some of the basic statistical concepts – means, standard deviations, and distributions – and how they can be used to describe the results obtained from a bioassay. Then, we described how we can investigate the distribution of our sample-based estimates…
A common discussion we at Quantics have with our clients surrounds the issue of pseudo-replicates. It’s an area of tension between scientist and statistician – pseudo-replicates reduce the cost of an assay, but also its statistical validity, meaning that a compromise solution is often required. One such solution is averaging pseudo-replicates, which comes with its…
In part 1 of our series covering the confidence interval, we examined some of the basic statistical concepts associated with a bioassay. In particular, we saw that a property of interest – we considered (and will continue to consider!) the EC50 of a test lot – follows a distribution defined by a mean (\(\mu\)) and…
A crucial acknowledgement of the scientific method is that no measurement will ever be perfect: results will always have associated variability, no matter how sophisticated the methodology used. Bioassay is no exception, so it is not surprising that one of the most common areas we address at Quantics is how to account for this uncertainty….
A clinical trial is often designed to demonstrate that a new treatment is performing better than the currently available treatment. To do this, one must show that there is a positive difference between the new and old treatments, and that this difference is statistically significant. To determine statistical significance, we use statistical hypothesis testing procedures….