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Elementary Statistics (Math 145) September 8, 2010
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Statistics is the science of collecting, analyzing, interpreting, and presenting data. is the science of collecting, analyzing, interpreting, and presenting data. Two kinds of Statistics: 1. Descriptive Statistics. 2. Inferential Statistics. A statistical inference is an estimate, prediction, or some other generalization about a population based on information contained in the sample. Use a representative sample.
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Sampling Designs 1. Simple Random Sampling. 2. Systematic Random Sampling. 3. Cluster Sampling. 4. Stratified Random Sampling with Proportional Allocation.
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Simple Random Sampling A sampling procedure for which each possible sample of a given size has the same chance of being selected. Population of 5 objects: {A, B, C, D, E} Take a sample of size 2. Possible samples: {(A,B), (A,C), (A,D), (A,E), (B,C), (B,D), (B,E), (C,D), (C,E), (D,E)} Random number generators
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Systematic Random Sampling Step 1. Divide the population size by the sample size and round the result down to the nearest number, m. Step 2. Use a random-number generator to obtain a number k, between 1 and m. Step 3. Select for the sample those numbers of the population that are numbered k, k+m, k+2m, … Expected number of customers = 1000 Sample size of 30 m = 1000/30 = 33.33 33 Suppose k = 5. Then select {5, 5+33, 5+66, …}
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Cluster Sampling Step 1. Divide the population into groups (clusters). Step 2. Obtain a simple random sample of clusters. Step 3. Use all the members of the clusters in step 2 as the sample.
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Stratified Random Sampling with Proportional Allocation Step 1. Divide the population into subpopulations (strata). Step 2. From each stratum, obtain a simple random sample of size proportional to the size of the stratum. Step 3. Use all the members obtained in Step 2 as the sample. Population of 9,000 with 60% females and 40% males Sample of size 80. 48 females (from 5,400) and 32 males (from 3,600).
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Homework Chapter 1 : (pp. 18) # 1, 2, 5, 7, 10.
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