Statistical Inference Estimation Lecture Notes

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          Notes in lectures although you may wish to annotate the typed notes and examples as you become. This is an important and common statistical decision, which should be given due consideration, since an inadequate sample size invariably leads to wasted resources.

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          CI serves to reject not only a null hypothesis based on a difference of zero, but also a null hypothesis, in respect to this particular sample, based on any population difference outside the limits of the CI.

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          This is called statistical inference.

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          Optimization methods and regularization. Hypothesis testing and estimation are two alternative approaches to statistical inference We looked at estimation in the last lecture In general.

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          Bootstrapping means you take repeated samples from a sample and then make statements about a population. Relative efficiency is often management issues that the approximation to move forward this kind of values of possible errors or anova technique could not able to order.

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          See that in large samples, many sampling distributions can be approximated with a normal distribution. If there is a close agreement between the two cumulative distributions, the hypothesis that the sample was drawn from population with a normal distribution function is supported.

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      • Otherwise, we can do ANOVA and regression without any assumptions, and the numbers come out the same. Be familiar with the concept of sufficiency and the likelihood principle Know the most important estimation methods like maximum likelihood least square and the.

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          • The next few slides list common measures of central tendency and spread.
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          • Very small n produces power so low that false hypotheses are accepted.
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          Parameter Expansion and Efficient Inference. Knowing these two facts gives us ample information to make statements about the probability of observing a certain value within that distribution.

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          • Outlier detection in the single population setting is not too difficult.