Chapter 9 Sampling Distributions and Confidence Intervals for Proportions.pdf

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9.1 - The Distribution of Sample Proportions True proportion is denoted p Two possible outcome: Success Failure P^ is the notation for proportion of the random sample to the true value 9.2 - Sampling Distributions for Proportions Sampling Distribution - The distribution of sample proportions over all possible independent samples from the same population ࠵?࠵?#࠵? %&’ ( = * ࠵?࠵? ࠵? Sampling Error - The difference between sample proportions Can also be seen as sampling variability Sampling distribution model for the Sample Proportion - ࠵?(࠵?, * 12 3 ) How Good is the Normal Model? Claim is only approximately true Assumptions and Conditions Independence Assumption - Sample values must be independent of each other Sample Size Assumption - Sample size, n, must be large enough Randomization Condition - Sample must be a simple random sample 10% Condition - If sampling is not made with replacement, then the population must bot be larger than 10% of the population