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7.SP.C.5.TheoreticalProbability1
7.SP.C.5.TheoreticalProbability1

2 - lecturemania
2 - lecturemania

SAS Essentials III: Statistics for Hamsters
SAS Essentials III: Statistics for Hamsters

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Introduction to Probability Theory, Algebra, and Set Theory

... 1. Show that the expected value of the indicator function of A is the probability of A. 2. Express the indicator functions for A ∩ B, A ∪ B and Ac through the indicator functions for A and B. Answer. Let X be the indicator function for A. Then E[X] = 0 · P ({X = 0}) + 1 · P ({X = 1}) = P ({X = 1}) = ...
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... Operations and Algebraic Thinking: Use the four operations with whole numbers to solve problems. Gain familiarity with factors and multiples. Generate and analyze patterns. Number and Operations in Base Ten: Generalize place value understanding for multi-digit whole numbers. Use place value understa ...
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... 7.1 Random Phenomena and Probability With random phenomena, we can’t predict the individual outcomes, but we can hope to understand characteristics of their long-run behavior. For any random phenomenon, each attempt, or trial, generates an outcome. We use the more general term event to refer to out ...
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Exploring Data PowerPoint

File
File

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History of statistics

The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, ""statistics"" means both sets of collected information, as in national accounts and temperature records, and analytical work which requires statistical inference.Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.A number of statistical concepts have had an important impact on a wide range of sciences. These include the design of experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.
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