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This lecture covers the basics of probability, including the naive definition and its applications in various disciplines. The lecture also covers the mathematics behind probability, and how to apply it to real life situations.

**00:00:00**The speaker discusses the importance of practice in learning, and goes on to discuss the style of homework and how to write an argument. The review is also mentioned.**00:05:00**In this lecture, Professor Bowers covers the basics of probability, including the naive definition and applications in physics, quantum mechanics, genetics, economics, game theory, and other disciplines. He also mentions that history is a field where probability is often used. Finally, he informs students that they are allowed to take the course pass/fail and that this allows for greater flexibility in pursuing their academic interests.**00:10:00**This lecture discusses the origins of probability, which can be traced back to gambling. The course then delves into the mathematics behind probability, which is necessary for understanding how to apply it to real life situations.**00:15:00**In this lecture, Professor Cox describes a sample space and event, and explains how they are related. He also reviews some of the basics of set theory and probability. He states that most of what students learn in a calculus class is not as counterintuitive as what they will encounter in this course.**00:20:00**The naive definition of probability is to count the number of favorable outcomes in a sample and divide by the number of possible outcomes. This definition has a huge assumption that all outcomes are equally likely and that there are finitely many outcomes.**00:25:00**In this lecture, Professor Rose explains the basics of counting, including the principle of the multiplication rule and how it can be used to calculate the numerator and denominator of a fraction. He also discusses how calculus is not a prerequisite for this material, and goes on to introduce the concept of permutations and combinations.**00:30:00**In this lecture, the author explains how to calculate the probability of a particular outcome in a series of experiments, using the multiplication rule. The example given is the probability of a full house in poker.**00:35:00**In this lecture, the instructor explains the definition of a full house, and how to calculate the probability of obtaining one. He also notes that the probability of any given hand can be calculated using the multiplication rule.**00:40:00**The binomial coefficient, or "n choose k," is the number of ways to choose k out of n things. This number is easy to remember if you think in terms of the tree structure of multiplication. Order matters when sampling, and this is immediately apparent in the equation n choose k = n to the k factorial.**00:45:00**The first lecture of Statistics 110 covers topics such as probability and counting. This is followed by a summary of what is needed for the homework. Normally, by the end of the lecture, most of the homework has been covered. However, due to a holiday, a few loose ends will be addressed next week.

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