GradeBuddy AEM 201 1ST EditionExam #3 Study Guide: Lecture Chapters 7-8CHAPTER 7: METHODS OF SAMPLING AND SAMPLINGDISTRIBUTIONS- Point Estimationo Commonly used point estimators:- Accuracy vs. Precisiono Accuracy: the correctness of an estimatoro Precision: the exactness of an estimatoro Precision and accuracy are inversely related. If you want more of one you must give up some of the other- Important Characteristics of Point Estimatorso Unbiasedness: the expected value of the sample (point) estimators (statistic) equals the population valueo Efficiency: if two (or more) estimators produce unbiased estimates of the same parameter, the estimator with the smaller (smallest) standard error is said to have greater (greatest) efficiencyo Consistency: the probability that the value of the point estimate falls within some given range about the parameter increases to 1 as sample size growso Sampling Error: the difference between an unbiased point estimator and the actual value of the parameter being estimatedo The mean and the proportion are the unbiased point estimators of the population- Sampling Distribution of the Sample Meano Expected Value of the Mean The expected value of the mean is equal to the population meano Standard Error:GradeBuddy oo Central Limit Theorem: when selecting a simple random sample from a population the sampling distribution of the sample mean can be approximated by a normal probability distribution as the sample size becomes large no matter how the original population is distributed Any sample of 30 or greater is sufficient to assure that the central limit theorem will force the potential values of the sample mean to be normally distributed- Sampling Distribution of the Sample Proportiono Expected Value of the Proportion The expected value of the proportion is equal to the population proportiono Standard Error: o Central Limit Theorem: when selecting a simple random sample from a population, the sampling distribution of the sample proportion can be approximated by a normal probability distribution as the sample size becomes larger as long as (np is greater than or equal to 5) and [n(1-p) is greater than or equal to 5]CHAPTER 8: INTERVAL ESTIMATION- Sampling Error: the absolute difference between a parameter and its point estimator- Confidence Level/Confidence Coefficient: the proportion of times a confidence interval can be expected to contain the true value of the parameter over many independent, identical, repeated trials. The correctness of an estimator. OR the probability that the interval estimation procedure will generate an interval that does contain the true value of the parametero 1-- Confidence Interval/Interval Estimate: range of values, used as an estimate fo a parameter that will contain the true value of the parameter a given proportion oftimes over many independent, identical, repeated trials.- Interval Estimation for the Population Mean When the Population Standard Deviation is Known and the Sample Mean is Normally DistributedGradeBuddy -- Interval Estimation for the Population Mean when the Population Standard Deviation is unknown and the Sample Mean is Normally Distributed- Interval Estimation for the Population Proportion when Sample Proportion is Normally Distributed - Sample Size Estimation for the Population