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A First Course in Probability Models and Statistical by James H.C. Creighton

By James H.C. Creighton

Welcome to new territory: A path in likelihood types and statistical inference. the idea that of likelihood isn't really new to you after all. you might have encountered it because formative years in video games of chance-card video games, for instance, or video games with cube or cash. and also you find out about the "90% likelihood of rain" from climate stories. yet when you get past easy expressions of likelihood into extra sophisticated research, it truly is new territory. and intensely overseas territory it's. you want to have encountered experiences of statistical leads to voter sur­ veys, opinion polls, and different such reports, yet how are conclusions from these reports acquired? how will you interview quite a few citizens the day prior to an election and nonetheless make certain rather heavily how HUN­ DREDS of hundreds of thousands of electorate will vote? that is facts. you will find it very fascinating in this first path to work out how a adequately designed statistical examine can in achieving a lot wisdom from such vastly incomplete details. it truly is possible-statistics works! yet HOW does it paintings? by way of the top of this direction you should have understood that and lots more and plenty extra. Welcome to the enchanted forest.

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The face is shaped differently from the tail. But such physical complications are beside the point! We know what we mean by fair and most coins, if they have not been damaged in some way, will be at least approximately fair. In the previous paragraph, we've described two practically related but logically distinct ideas of probability: probability as "long-run relative frequency" and probability as determined by symmetry. There are other notions of probability. There is probability as "degree of rational belief," the degree of belief a rational person would invest in a given statement.

B) Suppose you toss a fair coin many times, how many heads would you expect on average? (c) Suppose you toss a fair coin and that you'll be given two dollars if you toss a head and three dollars if you toss a tail. How much money would you expect to take in on average? (d) Now suppose you toss a coin which comes up heads 90% of the time. If you're given two dollars for a head and three dollars for a tail, how much money would you expect to take in on average? (e) Verify that your "take" in part (c) is a random variable.

B) Suppose on this die the face with one dot comes up half the time and all the other faces are equally likely. How risky is the game? (c) In part (b), because half the probability for the die is concentrated on the single value "one dot," this game should be LESS risky than the same game with the fair die. But we showed that it's MORE risky! What's wrong? " A coin is fair if, "in the long run," heads should show uppermost half the time. This is justified if we think the coin is symmetric. Of course, no physical object is perfectly symmetrical, and for that reason, no physical coin is exactly fair.

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