Lecture_09_26

Lecture_09_26 - Lecture of September 26 HW#3 due HW#4...

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1 Lecture of September 26 Lecture of September 26 • HW#3 due. HW#4 assigned today and due in class on 10/03.
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2 Where we are? Where we are? Goal: Statistical Control of Quality Variation reduction How to describe variation theoretical model for population probability distribution discrete continuous tell us what the system is supposed to be empirical/numerical model for sampled data histogram, sample mean sample variance, etc. tell us what the system actually is compare make conclusion about a process
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3 Need for Statistical Inference Need for Statistical Inference • In reality we do not know the true distribution of a process. What we have to rely on is the data collected from a process. • What we can do is to collect a random sample of n observations, { x 1 , x 2 , …, x n }, that represents a portion of much larger, real or hypothetical population. Then, we make inference about the theoretical model based on our limited sample observations. • We will assume the type of population distribution (be it normal, Binomial, Poisson). Then, we only need to specify or estimate the parameters in order to completely determine the entire distribution.
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Lecture_09_26 - Lecture of September 26 HW#3 due HW#4...

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