Can Statistics Tell Us If Dinosaurs Had Feathers?

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Recently dr. Gabriela Haynes published an article explaining why feathered dinosaurs are not viable and why creationists are unwise to embrace the concept. Morphology-based statistical baraminology is one of the reasons some creationists do it. Statistical baraminological analyzes have been used to argue that dinosaurs had feathers.1 However, morphological statistical baraminology carries significant baggage and numerous unwarranted assumptions.2

First of all, it is important to distinguish between actual baraminology and statistical baraminology. Baraminology, the study of created species, is a valid creationist field of study. Statistical baraminology is a subset of baraminology proper that uses statistical methods to try to determine the limits of created species. The majority of these studies are based on morphology, although DNA-based studies are becoming more common. There are other methods of baraminology as well, including hybrid studies—which is the biblical way of defining species (Genesis 6:19, 8:17)—and the cognitum method3 that Answers in Genesis used to use hybrid studies in determining species to add ark species. 4 However, statistical baraminology has been the dominant method in this field for the past two decades.

The first proposal to use statistics to define species came in 1990.5 Before that, baraminology had been content with hybrid studies, as proposed by baraminology’s founder, Frank Marsh.6 The call for the use of statistics was made in 1998 with a study on catarrhines -Primates updated .7 This study implemented something known as Baraminic Distance Correlation (BDC). This correlation is visualized as dij=mij/nij Where i.e equal baraminic distance, m is the number of mismatched characters, and n is the total number of characters compared. While distance is interesting, there is a basic assumption here – that similarity equals descent.

Creationists are no doubt familiar with the homology argument often advanced by evolutionists, namely that if two living things look alike, they probably descended from a common ancestor. Basically, the BDC equation makes the same assumption—the more similar two organisms are, the more closely related they are. Obviously this is wrong. A similar design may indicate common ancestry, but more often it simply indicates a common design source. However, the BDC equation starts from an assumption that defies nearly a century of creationist arguments and remains the fundamental driving assumption of morphological statistical baraminology.

Reliable data source?

Like all other statistical measurements, statistical baraminology relies on its data. Nevertheless, almost all of its dates come from evolutionary phylogenetic data. That doesn’t necessarily mean it’s bad or wrong, just that it should be treated with skepticism. In statistical baraminology, however, the data are often treated as sacrosanct. Any question of bias is dismissed unless it can be proven.8 Yet evolutionists themselves admit that they approach their phylogenetic analysis with prejudice!9 Everyone has a worldview, and that worldview affects their data collection as well as theirs data interpretation.

Even if the data is chosen impartially, there is another problem. The basic assumption of continuity and discontinuity is problematic. According to the paradigm of statistical baraminology, organisms within a species should share continuity with other members of the species and be discontinuous with everything else. This discontinuity must be statistically significant and holistic. Without getting into the statistical weeds, statistical baraminology requires statistically significant results that depend heavily on character selection.10 Yet characters are chosen by evolutionists for the purpose of constructing a universal tree. Characters that create continuity are likely to be favored by default. Because significance is so difficult to achieve, holism was emphasized for a time, but even that was abandoned. The statistical baraminological literature effectively abandoned it by 2010, when a particular baraminological study attempting to expand human baramin was postponed Australopithecus sediba into the human baramin based solely on cranial features.11 A similar agenda-driven paper was moving Homo naledi12 into human baramin based on the same traits, and although a later publication using more holistic data showed that it did not cluster with humans,1314 statistical baraminologists still consider it H. naledi Human.15

Importantly, morphology-based statistical baraminology has only been applied to humans once, and that was the first paper, published in 1998.16 In that paper, the method failed to separate monkeys and humans until over half of the data was discarded. Since then there has been no repetition. However, it is not as if there is no data available for comparison. For example, two years before the debut of morphological statistical baraminology, a paper was published comparing humans to modern apes and monkeys using 264 characters—17 apes and monkeys, humans, and 4 outgroups for a total of 22 taxa.17 Other papers are undoubtedly as available good.

What results do we get if we consider all the premises of statistical baraminology and use the most up-to-date software? Under no circumstances can we separate humans from apes. In both the Baraminian distance plots (Figures 1, 3) and the MDS plots (Figures 2, 4), humans group with great apes.

Figure 1. Baraminic distance correlation graph of monkeys, apes and humans. Black squares indicate significant continuity, open circles indicate significant discontinuity.

figure 2

Figure 2. MDS diagram of monkeys, apes and humans. The black dot is genus homo (People).

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Figure 3. Baraminic distance correlation graph of great apes and humans, including outgroups.

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Figure 4. MDS diagram of great apes and humans. Black is genus homo (Person). The next points represent the genera gorilla and Pan (gorillas and chimpanzees).

This is a significant problem. If the data are reliable and the method works, as proponents of statistical baraminology claim, we should be able to reliably separate great apes from humans. After all, this is the one kind of limit that is clearly told to us in Scripture. Humans and apes have no common ancestors. However, according to statistical baraminology, they are of the same species. Is the method to blame, or the data—or both? Without further testing, we can’t be sure. It is likely that the answer is partly both.

Creationists should carefully analyze any statistical baraminology results and ensure that their results do not conflict with Scripture, known facts, and common sense before accepting them.

The bigger problem here isn’t just statistical baraminology – although that’s a big problem. The bigger problem is the importation of evolutionary assumptions into creation science and the unquestioning acceptance of what evolutionists produce and attempts to incorporate it into the creation model. like dr Haynes pointed out in her article, just because a creationist says it’s true doesn’t mean it’s true or that we should agree with it. It’s important to analyze everything critically, even if it comes from someone you think is on your side. Unfortunately, the lack of critical analysis drives statistical baraminology, essentially driving a cult of creation scientists dubbed “young-Earth evolutionists.”18 One even argues that we should use that term evolution to talk about creation.19 Creationists should carefully analyze all results of statistical baraminology and ensure that their results do not conflict with Scripture, known facts, and common sense before accepting them.

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