Note. This is a semi-independent summary of the same paper that Marty wrote about in the post here. I wrote it to present a different perspective on an otherwise fascinating idea. There is an increasing awareness and deep concern that most scientific findings are not reliable or valid. Many key researchers and research groups have called for (1) greater transparency
Read more
Researchers often use statistical tests to test hypotheses and/or infer properties of a population based on properties of a sample. A key idea is that all statistical tests assume a statistical model provides a complete and valid representation of variability in the data, and faithfully reflects how the study was conducted and the phenomena being tested. For example, when we
Read more
The scientist’s lab notebook is essentially a record of all scholarly activities conducted. However scientists often find it difficult to keep, or know how to keep, a good lab notebook. In 2015, PLoS published an editorial providing guidance on how to keep a good lab notebook. Here is a summary of a few key points: Record all scientific activities in
Read more
Sometimes we would like to focus more on some data and less on others, but still provide a visual display. The matplotlib function gridspec allows subplots of unequal size to be plotted on the same figure. How this function can be applied will be demonstrated using simulated data. Let’s simulate some common probability distributions of different statistics using Python’s numpy.random
Read more
In hypothesis testing, the number of samples needed to find an effect depends on the: size of the effect variability of the effect tolerance to reporting a false positive (Type I error) and probability of not reporting a false negative (1 – probability of Type II error) The following code uses the stats package in R to calculate sample size
Read more
Many research questions investigate how outcomes change (over time) in response to different test conditions or treatments. Participants are randomised into groups to receive a test condition or treatment to make the groups comparable in every way except the test condition or treatment that is received. Consequently, comparing outcomes between groups allows us to understand how outcomes change under different
Read more
Scientifically Sound 