I had low expectations for this book. It was assigned for some humanities class im taking (Studium generale). However, the book is a quite decent introduction to the field. Happily surprised.<\/p>\n
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http:\/\/libgen.org\/book\/index.php?md5=7d804c1413f8993654ecc933170a5141<\/a><\/p>\n <\/p>\n –<\/p>\n <\/p>\n The first two statements are called the premisses of the inference, <\/span><\/p>\n while the third statement is called the conclusion. This is a <\/span><\/p>\n deductive inference because it has the following property: if the <\/span><\/p>\n premisses are true, then the conclusion must be true too. In other <\/span><\/p>\n words, if it\u2019s true th at all Frenchman like red wine, and if it\u2019s true <\/span><\/p>\n th at Pierre is a Frenchman, it follows th at Pierre does indeed like <\/span><\/p>\n red wine. This is sometimes expressed by saying th at the <\/span><\/p>\n premisses of the inference entail the conclusion. Of course, the <\/span><\/p>\n premisses of this inference are almost certainly not true – there <\/span><\/p>\n are bound to be Frenchmen who do not like red wine. But that is <\/span><\/p>\n not the point. What makes the inference deductive is the <\/span><\/p>\n existence of an appropriate relation between premisses and <\/span><\/p>\n conclusion, namely th at if the premisses are true, the conclusion <\/span><\/p>\n must be true too. Whether the premisses are actually true is a <\/span><\/p>\n different matter, which doesn\u2019t affect the status of the inference as <\/span><\/p>\n deductive.<\/span><\/p>\n <\/p>\n This distinction is not a good idea. In that case, the existence of a deductive and invalid argument is impossible. I wrote about this area years ago, but apparently never finished my essay, or published it. It is still on my desktop.<\/p>\n <\/p>\n –<\/p>\n <\/p>\n Philosophers of science are interested in probability for two main <\/span><\/p>\n reasons. The first is th at in many branches of science, especially <\/span><\/p>\n physics and biology, we find laws and theories th at are formulated <\/span><\/p>\n using the notion of probability. Consider, for example, the theory <\/span><\/p>\n known as Mendelian genetics, which deals with the transmission <\/span><\/p>\n of genes from one generation to another in sexually reproducing <\/span><\/p>\n populations. One of the most important principles of Mendelian <\/span><\/p>\n genetics is that every gene in an organism has a 50% chance of <\/span><\/p>\n making it into any one of the organism\u2019s gametes (sperm or egg <\/span><\/p>\n cells). Hence there is a 50% chance th at any gene found in your <\/span><\/p>\n mother will also be in you, and likewise for the genes in your <\/span><\/p>\n father. Using this principle and others, geneticists can provide <\/span><\/p>\n detailed explanations for why particular characteristics (e.g. eye <\/span><\/p>\n colour) are distributed across the generations of a family in the <\/span><\/p>\n way that they are. Now \u2018chance\u2019 is ju st another word for <\/span><\/p>\n probability, so it is obvious th at our Mendelian principle makes <\/span><\/p>\n essential use of the concept of probability. Many other examples <\/span><\/p>\n could be given of scientific laws and principles th at are expressed <\/span><\/p>\n in terms of probability. The need to understand these laws and <\/span><\/p>\n principles is an important motivation for the philosophical study of <\/span><\/p>\n probability.<\/span><\/p>\n <\/p>\n Author forgot about sex-linked genes, which complicate matters.<\/p>\n <\/p>\n –<\/p>\n <\/p>\n Modern science can explain a great deal about the world we live in. <\/span><\/p>\n But there are also numerous facts th at have not been explained by <\/span><\/p>\n science, or at least not explained fully. The origin of life is one such <\/span><\/p>\n example. We know that about 4 billion years ago, molecules with <\/span><\/p>\n the ability to make copies of themselves appeared in the primeval <\/span><\/p>\n soup, and life evolved from there. But we do not understand how <\/span><\/p>\n these self-replicating molecules got there in the first place. Another <\/span><\/p>\n example is the fact th at autistic children tend to have very good <\/span><\/p>\n memories. Numerous studies of autistic children have confirmed <\/span><\/p>\n this fact, but as yet nobody has succeeded in explaining it.<\/span><\/p>\n <\/p>\n https:\/\/en.wikipedia.org\/wiki\/Autism_and_working_memory<\/a><\/p>\n <\/p>\n Wiki seems to be of the exact opposite opinion.<\/p>\n <\/p>\n –<\/p>\n <\/p>\n Since the realism\/anti-realism debate concerns the aim of science, <\/span><\/p>\n one might think it could be resolved by simply asking the scientists <\/span><\/p>\n themselves. Why not do a straw poll of scientists asking them about <\/span><\/p>\n their aims? But this suggestion misses the point – it takes the <\/span><\/p>\n expression \u2018the aim of science\u2019 too literally. When we ask what the <\/span><\/p>\n aim of science is, we are not asking about the aims of individual <\/span><\/p>\n scientists. Rather, we are asking how best to make sense of what <\/span><\/p>\n scientists say and do – how to interpret the scientific enterprise. <\/span><\/p>\n Realists think we should interpret all scientific theories as<\/span><\/p>\n attempted descriptions of reality; anti-realists think this <\/span><\/p>\n interpretation is inappropriate for theories th at talk about <\/span><\/p>\n unobservable entities and processes. While it would certainly be <\/span><\/p>\n interesting to discover scientists\u2019 own views on the realism\/anti- <\/span><\/p>\n realism debate, the issue is ultimately a philosophical one.<\/span><\/p>\n <\/p>\n Good idea. Is that a case for expertimental filosofy?<\/p>\n <\/p>\n Cudnt find any data from a quick google.<\/p>\n <\/p>\n –<\/p>\n <\/p>\n Cladists argue th at their way of classifying is \u2018objective\u2019 while th at of <\/span><\/p>\n the pheneticists is not. There is certainly some tru th in this charge. <\/span><\/p>\n For pheneticists base their classifications on the similarities <\/span><\/p>\n between species, and judgements of similarity are invariably partly <\/span><\/p>\n subjective. Any two species are going to be similar to each other in <\/span><\/p>\n some respects, but not in others. For example, two species of insect <\/span><\/p>\n might be anatomically quite similar, but very diverse in their <\/span><\/p>\n feeding habits. So which \u2018respects\u2019 do we single out, in order to<\/span><\/p>\n make judgements of similarity? Pheneticists hoped to avoid this <\/span><\/p>\n problem by defining a measure o f \u2018overall similarity\u2019, which would <\/span><\/p>\n take into account all of a species\u2019 characteristics, thus permitting <\/span><\/p>\n fully objective classifications to be constructed. But though this idea <\/span><\/p>\n sounds nice, it did not work, not least because there is no obvious <\/span><\/p>\n way to count characteristics. Most people today believe that the very <\/span><\/p>\n idea o f \u2018overall similarity\u2019 is philosophically suspect. Phenetic <\/span><\/p>\n classifications do exist, and are used in practice, but they are not <\/span><\/p>\n fully objective. Different similarity judgements lead to different <\/span><\/p>\n phenetic classifications, and there is no obvious way to choose <\/span><\/p>\n between them.<\/span><\/p>\n <\/p>\n Surely someone has tried factor analysis to find this overall similarity factor, if there is one? It’s not that hard to find out. Make a huge list of things to measure to species. Measure it all in say, 1000 species, and then factor analyze it. Is there an overall factor similar to g<\/em><\/a>? If not, then the hypothesis is disconfirmed.<\/p>\n <\/p>\n