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Hypothesis Testing

# Hypothesis Testing - Hypothesis Testing Estimation...

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Hypothesis Testing & Estimation Economists are often engaged in estimation and hypothesis testing. One of the key points in statistics is the difference between a population and a sample. Population: All the members of a certain class or group. Populations may be finite or infinite. A parameter, usually in Greek letters, represents the characteristics of a population. Sample: A portion of the population. A statistic, usually in English letters, represents the characteristics of a sample. Normally we are trying to use a sample to make an inference about a population. (If we knew the values for the population we wouldn’t need a sample). An estimate is an educated “guess” about the value of a parameter. Usually we use statistics to estimate parameters. Estimate can either be: Point estimates – a single value. For example a sample mean is a point estimator of a population mean Interval estimator – a range of values that we believe the parameter lies inside. (It is unlikely that a point estimator is exactly correct). To do estimates, we need to know how the samples are likely to be distributed. We will use the sample mean since it is the simplest.

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