sLecture1cPBS - Lecture#1 Learning Objectives 1 Know what...

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Lecture #1 Learning Objectives 1. Know what simple random sampling is and how simple random samples are selected. 2. Understand the difference between a parameter and a statistic. 3. Understand the concept of a sampling distribution. 4. Know the Central Limit Theorem and the important role it plays in sampling. 5. Know the characteristics of the sampling distribution for the sample mean. 6. Know the definition of the following terms: Population Sample (Simple Random) Parameter Statistic Sampling With Replacement Sampling Without Replacement Point Estimator Sampling Distribution Standard Error Finite Population Correction “Get your facts first, and then you can distort them as much as you please.” - Mark Twain (1835 – 1910)
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BM330 – Lecture #1 1 Sampling Distributions Why do we care about “sampling distributions”? To begin to answer this question, we will consider the following business scenario. Mini-Case: The Unlimited Avenue A major retail company plans on opening a new chain of up-scale stores called the Unlimited Avenue ” shop. Unlimited Avenue is intended to market higher-end woman’s fashions. This is a high risk venture for two reasons. First, woman’s fashions at this level can be considered perishable in the sense that as soon as the current fashion changes, any existing inventory loses considerable value. Second, stores at this level should be opened only in geographical areas where the background population has sufficient income to make the operation a going concern. We will focus on the latter issue. It is anticipated that the minimum average household income in the relevant region needed to make any given store location successful must exceed $50,000. Prior to opening the store, the corporate research staff will attempt to determine the average annual household income within a 25 mile radius of the expected store location. In order to know the population mean, a census would have to be taken.
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BM330 – Lecture #1 2 What are the drawbacks of collecting census information? What other option does the research staff have? By using sampling methods , we can estimate the average population income level to any reasonable degree of accuracy and precision required. To understand how to create estimates of population descriptors that have a measure of accuracy associated with them, we need to understand sampling distributions. Populations, Samples, and Sampling Distribution s Population vs. Sample: A population is A sample is We use measures of central tendency (location), dispersion (spread), skewness, etc. to summarize data. Examples include
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BM330 – Lecture #1 3 Parameters vs. Statistics: Parameters are S tatistics are Sampling Methods: Probabilistic vs. Non-probabilistic The statistical tools that we will learn about in this course generally require that the method used to select a sample is simple random sampling . In order for a sample to be a simple random sample (s.r.s.), the elements included in the sample must be selected to satisfy both of the following conditions.
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sLecture1cPBS - Lecture#1 Learning Objectives 1 Know what...

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