endobj 76 0 obj Here are some helpful study tips to help you get well-prepared for a probability exam. Pre-made digital activities. 100 0 obj Then Pr[X ^Y] is the probability that the die lands two and that it is even (which is just the probability that it is two), so 1=6. (Discrete random variables) Nathan Ferguson. P(not graduate) = 1 - P(graduate) = 1 - 0.9 = 0.1. A math teacher gave her class two tests. Great for an accommodation for special education students. Providing students an opportunity to apply the laws of probability to real-world scenarios is essential in deepening their understanding of the concepts. /Filter /FlateDecode (2) P(A0) = 1 P(A) ( A0 is the complement of A). << by. When we will want to be explicit about the probability . Wx6I)O{-UuUg D}!Tdfy*f(Qlvg;l!->,OA|yGnC}B'MZk^)F$\mU|I_y0yc((&\H sA&z8*u>KR|HsW;}i (Writing short proofs) ","noIndex":0,"noFollow":0},"content":"Successfully working your way through probability problems means understanding some basic rules of probability along with discrete and continuous probability distributions. endobj << /S /GoTo /D (chapter.7) >> /Type /ObjStm Most comprehensive Probability Distribution Cheat Sheet. For a . PROBABILITY CHEAT SHEET BASIC PROBABILITY RULES WITH EXAMPLES Complement Rule = ( ) ( ) means "not A" The probability 4.2 Process Theresultofright-multiplyingavector v 2Rm (or, equally, v 2R1 m) byamatrixW 2Rm n isavector y 2Rn - v W = y - notehowthematchingdimensionsm are'self-destroyed'. 25 0 obj we can use a prediction based on experimental or theoretical probability. Similarly throwing a dice, where we have 6 values for a random variable and so Binomial . The probability that Anya will graduate high school is 0.9. Event Any subset $E$ of the sample space is known as an event. Sequences and Series They have a high probability of being on the exam.
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The relationship between mutually exclusive and independent events
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Identifying when a probability is a conditional probability in a word problem
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Probability concepts that go against your intuition
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Marginal, conditional, and joint probabilities for a two-way table
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The Central Limit Theorem:
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When to use a permutation and when to use a combination
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Finding E(X) from scratch and interpreting it
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Sampling with replacement versus without replacement
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The Law of Total Probability and Bayes’ Theorem
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When the Poisson and exponential are needed in the same problem
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