Warts from Touching a Toad

Determinism is a philosophical view holding that all events are dependent completely on previously existing causes, and if we could set up identical conditions for another run, we would always get identical results. It has been debated for millennia.

Underdetermination happens when the available evidence is insufficient to determine which conclusion we can reach. Some philosophers make a case that all conclusions are underdetermined in one manner or another. See https://ephektikoi.wordpress.com/2020/07/16/underdetermination/ for more discussion.

Confounding factors are those not currently under investigation that may have caused the result. The interpretation of the study results is thus ambiguous. Confounding factors in research are also called 'confounds' for brevity.

Coincidence is seen when there is no causality, but there appears to be a pattern of causality

We really want to establish the truth, accuracy, or reality of research claims. One method that is supposed to be used, but seldom is, is replication of the study. By replication, the researcher hopes to obtain the same results. In practice, replication is seldom done. Apparently replication research seldom gets funded, and replication studies seldom get published. When replication has been attempted to see how well research has been done, they have frequently found that studies are not replicated at a very satisfactory rate. This is still an ongoing area for debate. It has been termed the replication crisis. See for instance https://www.embopress.org/doi/10.15252/embr.201744876, https://www.nature.com/collections/prbfkwmwvz/ and this https://www.wyatt.com/blogs/quality-standards-for-the-life-sciences-pqs.html.

Ethics committees examine proposed research to determine if ethical guidelines for the institution and the discipline will be adhered to. These guidelines can apply to both human and animal research subjects.

Scientific knowledge is disseminated in various ways. These include:

1. Conferences where there is the presentation of papers.
2. Informal exchanges of information among experts such as informal get-togethers, colloquia, and chats over drinks.
3. Papers peer reviewed and formally published in research journals.
4. Scholarly visits, where researchers may come from another institution for a period of time, maybe for a research sabbatical.
5. Formal and informal teaching, where experts systematically explain the body of knowledge of their discipline.

There are problematic aspects to many of these activities, and the progress of science is undoubtedly retarded because of them.

The peer review of journal articles prior to publication is supposed to make sure that research is reasonably sound, and that the results may be trusted. The peer review process is unfortunately flawed. Research studies make it through the peer review process without being properly vetted in numerous cases. On the other hand, it tends to filter out studies which challenge accepted dogma. There are numerous critiques of the peer review process, and these can be readily found through Internet searching. See for instance https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197125/

Statistics is a difficult mathematical study for most of us. I am not going to try to teach anyone statistics; that would be foolish. I am going to present as clearly and as briefly as I can some of the important ideas. This is a very cursory overview. Don't take any of this as gospel; it has been decades since I formally studied the subject, and statistics for me was three courses and a few years running data through computer programs, not a deep study.

Statistics can be broken into two major areas, descriptive statistics and inferential statistics. I will give a quick explanation of each below.

Inferences can be made from the results in a sample to the population at large using probabilistic methods, statistical inference.

Statistics starts with measurement. There must be some scale or metric, and there must be a device for making the measurement. There will be some error in any measurement; we and our machines are not perfect. There will also be some variability in the measure, since the world seems to give us variable results, even when we are trying to be very careful. Some type of measurements are horrible in this regard, some are not.

There are three sorts of scales used in measurement for statistical purposes. These are categorical, ordinal, and continuous. For more information, see: https://www.scalelive.com/scales-of-measurement.html

Measures taken of some factor of interest are called variables. Variables that we wish to study as outcomes of manipulations are termed dependent. Variable which we wish to manipulate to see their effect on outcomes are called independent. Experimental studies aim to determine how changes in the value of independent variables in a sample effect changes in the dependent variables in the sample. It is possible to investigate if the relationships are causal.

There are three types of measurements all called averages. The first, the mean, is what most of us think of as average. For this statistic, add up all the figures and divide by the number of figures. The second, the mode, is not so well known. It is the figure that occurs most often in the set of measurements. The third, the median, is also not well known. It is the number having half of the measurements lower, and half of the measurements higher.

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