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Medieval Icelandic literature is rich with animal references. We often read of characters appearing in dreams as animals, taking the shape of animals, or even simply fighting like ferocious beasts. Particularly prominent are the traditions of animal warriors, such as berserkir, and animal doubles embodied by fylgjur and those who are said to be hamrammr. Traces of these animal traditions can be found across the Old Norse sphere, but they are most persistent in the literature of Iceland. Despite the changes in perspective to pre-Christian material that took place over the centuries, the versatility of these animal traditions allowed them to remain current and relevant in Iceland. By conducting a study of the character Bǫðvarr bjarki, with particular focus on his shape changing episode in Hrólfs saga kraka, this thesis demonstrates the resilience and versatility that allowed these rich animal traditions to endure for centuries within the Old Norse-Icelandic context. Gjarnan er vísað til dýra í íslenskum miðaldabókmenntum. Oft koma sögupersónur fram í draumum sem dýr, taka á sig ásýnd dýra eða einfaldlega berjast eins og þau væru dýr. Einkar eftirtektarverðar eru frásagnir af hermönnum sem hafa dýrsleg einkenni, t.d. berserkir, en einnig fylgjur í gervi dýra auk þeirra persóna sem sagðar eru hamrammar. Menjar um þessa sagnahefð má finna víða í fornnorrænni menningu en eru mest áberandi í bókmenntum Íslands. Þó að afstaðan til hins forkristna efnis hafi breyst í gegnum tíðina, gerði sveigjanleiki sagnaminna um hamskipti af þessu tagi þeim kleift að halda gildi sínu í íslenskum bókmenntum eftir því sem sögu þeirra vatt fram. Með því að rannsaka sérstaklega sögupersónuna Bǫðvar bjarka og hamskiptum hennar í Hrólfs sögu kraka, er reynt í ritgerðinni að sýna fram á sveigjanleika en einnig varðveislu þessarar hefðar um aldaraðir í samhengi norrænna og íslenskra miðaldabókmennta.
In this section we ask and answer the following question. Suppose we assign a distribution function to a sample space and then learn that an event E has occurred. How should we change the probabilities of the remaining events? We shall call the new probability for an event F the conditional probability of F given E and denote it by P (F |E). Example 4.1 An experiment consists of rolling a die once. Let X be the outcome. Let F be the event {X = 6}, and let E be the event {X > 4}. We assign the distribution function m(ω) = 1/6 for ω = 1, 2,. .. , 6. Thus, P (F) = 1/6. Now suppose that the die is rolled and we are told that the event E has occurred. This leaves only two possible outcomes: 5 and 6. In the absence of any other information, we would still regard these outcomes to be equally likely, so the probability of F becomes 1/2, making P (F |E) = 1/2. 2 Example 4.2 In the Life Table (see Appendix C), one finds that in a population of 100,000 females, 89.835% can expect to live to age 60, while 57.062% can expect to live to age 80. Given that a woman is 60, what is the probability that she lives to age 80? This is an example of a conditional probability. In this case, the original sample space can be thought of as a set of 100,000 females. The events E and F are the subsets of the sample space consisting of all women who live at least 60 years, and at least 80 years, respectively. We consider E to be the new sample space, and note that F is a subset of E. Thus, the size of E is 89,835, and the size of F is 57,062. So, the probability in question equals 57,062/89,835 = .6352. Thus, a woman who is 60 has a 63.52% chance of living to age 80. 2 133
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