POLI 210 Lecture Notes - Lecture 13: Type I And Type Ii Errors, Descriptive Statistics, Null Hypothesis
21 Feb 2018
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Document Summary
Parameter: a number that describes a characteristic of our population. Statistic: any number that describes the data. Types of statistics: descriptive statistics: allows researcher to summarize the data in an effective and meaningful way, inferential statistics: allow for decisions or inferences from the data to a population based on interpretable pattern. Act of generalizing from a sample to a population with calculated degree of certainty. Our goal is to draw a random sample so that every unit in the population has an equal chance of being selected. Challenging factors: random digit dialing, web surveys, non-response issues. A well designed sample helps to ensure our estimate of the population parameter is accurate. More room for error with smaller sample. Even with random samples, our sample estimates are still subject to sampling variability. We can estimate the amount of variation expected from drawing repeated samples. The standard deviation of this theoretical sampling distribution is called the standard error.
