Having data is only half the battle. How do you know your data actually means something? With some simple Python code, you can quickly check if differences in data are actually significant. In ...

Learn about t-test assumption, including scale, sampling, normality, sample size, and variance equality, for accurate statistical analysis and reliable results.

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 ...

Advances in high-throughput biology and computer science are driving an exponential increase in the number of hypothesis tests in genomics and other scientific disciplines. Studies using current ...

In the realm of technical product development, hypothesis testing acts as a bridge between design, data and decision-making. It enables teams to move beyond assumptions and validate their ideas ...

Sankhyā: The Indian Journal of Statistics, Series B (1960-2002), Vol. 49, No. 3 (Dec., 1987), pp. 199-217 (19 pages) When a contingency table has many cells having very small frequencies, possibly ...

Rob Herbert does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

To establish whether clinical-product quality remains constant when making a process change can be a challenging exercise. Limited data availability further complicates the assessment of whether the ...