Statistics and Hypothesis Testing

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What is an estimator An estimator is a method of guessing a population parameter, for example, the population mean µ Y , using a sample of data. The estimate is the specific numerical guess that an estimator yields. Estimators of a parameter are indicated by inserting aˆ . For example, guesses about the population mean are labeled ̂µ Y
What would be a good way to guess µ Y One method of guessing the population mean is to take a sample <strong>and</strong> compute the sample mean: Y = ∑ n i=1 1 n Y i. Another way would be to take whatever observation happens to come first on the list, Y 1 (or last Y n ).
Page 1 and 2: Statistics and Hypothesis Testing M
Page 3: Summary of Main Points ◮ We will
Page 7 and 8: Y is the least squares estimator of
Page 9 and 10: Random Sampling The consequences of
Page 11 and 12: Hypothesis Testing 1. Gather a samp
Page 13 and 14: The p-Value p-value ≡ Pr H 0 [
Page 15 and 16: How likely is the observed value In
Page 17 and 18: Sample Variance, Sample Standard De
Page 19 and 20: Sample Standard Deviation The sampl
Page 21 and 22: Summary: Why standard error ◮ Can
Page 23 and 24: The Prespecified Significance Level
Page 25 and 26: An example Is the mean wage among r
Page 27 and 28: Average wage example, continued ◮
Page 29 and 30: Type I and Type II errors Null Hypo
Page 31 and 32: From Hypothesis Testing to Confiden
Page 33 and 34: Example: 95 percent CI In a sample
Page 35: Next time we do something from the

Statistics and Hypothesis Testing

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