Statistical Sciences 1024A/B Lecture Notes - Lecture 14: Sampling Distribution, Standard Deviation, Statistical Inference
20 Apr 2016
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Document Summary
Statistical interference provides methods for drawing conclusions about a population from sample data. Key assumption in statistical inference: the data comes from a random sample or from a randomized. Simple conditions for inference about a mean: we have an srs from the population of interest. There is no nonresponse or other periodical difficulty: the variable we measure has a perfectly normal distribution n( , in the population, we don"t know the population mean . But we do know the population standard deviation . The sampling distribution is narrower than the population distribution, by a factor of n. Thus, the estimate gained from our samples are always relatively close to the population parameter . If the population is normally distributed n( , so will the sampling distribution. Formulate: identify the parameter and choose a level of confidence. Solve: carry out work in two phases: check the conditions for the interval you plan to use, calculate the confidence interval.
