Explore essential statistical strategies for accurate protein quantification and differential expression analysis.

Basic concepts in hypothesis testing, including effect sizes, type I and type II errors, calculation of statistical power, non-centrality parameter, and applications of these concepts to twin studies.

Figure 1. (click to enlarge) Effect of temperature on seal strength. The green bars represent samples created using low temperature. The orange indicates packages created using the high-temperature ...

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by researchers to test predictions, called hypotheses. The first step in ...

It may be common knowledge that p < .05 indicates statistical significance. Psychology students (and others) are often taught that p < .05 means the probability (p) of rejecting the null hypothesis ...

Concern over the reliability of published biomedical results grows unabated. Frustration with this 'reproducibility crisis' is felt by everyone pursuing new disease treatments: from clinicians and ...