CRIM 320 Lecture Notes - Lecture 3: Confidence Interval, Interval Estimation, Statistical Inference

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January 24, 2017 lecture 3: distributions & statistical significance. Sampling distribution distribution of all possible sample outcomes for a statistic: one sample produces one statistics, mean is most common to summarize data. Standard deviation measures the variability/spread of a statistic: how its typically spread out around the mean, need a large number of samples to produce a distribution for the statistic. Standard error standard deviation of the sampling distribution: estimates the variability between samples; sd = measure the variability within a single sample. Frequency distribution summary depiction of how many times a particular value of a variable occurs. Sampling distribution a hypothetical distribution of all possible sample outcomes for a statistic: it is the bridge between the sample & the population. The binominal distribution 2 possible outcomes, ex. , flipping a coin, yes or no. Characteristics make it useful in application to research situations: many statistical have a sampling distribution that is approximately normal.

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