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A descriptive measure of a sample
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Statistic
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Method of organizing, summarizing, and presenting data
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Descriptive statistics
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The group of all items of interest
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Population
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The process of making an estimate. prediction, or decision about a population based on sample data
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Statistical inference
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A set of data drawn from a population
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Sample
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The data can be arranged in order & differences b/w data values are meaningful
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Interval scale
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The data consists of names, labels, or categories. There are no criteria for ordering the data from smallest to largest
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Nominal scale
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The data can be arranged in order & both & ratios b/w data values are meaningful. Also data has a true, absolute zero.
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Ratio scale
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The data can be arranged in order. However, differences b/w data values either can;t be determined or are meaningless
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Ordinal scale
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The Requirements of a Random Sample
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1. Each indiv. in population of interest must have an equal probability of being of being included in the sample 2. They all have equal chance of being picked
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Divide the entire population into pre-existing segments or clusters. The clusters are often geographic. Make a random selection of clusters. Include every member of each selected cluster in the sample.
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Cluster sampling
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Create a sample by using data from population members that are readily available.
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Convenience Sampling
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A simple random sample of n measurements from a population is a subset of the population selected in a
manner such that every sample of size n from the population has an equal chance of being selected.
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Simple Random Sampling
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Divide the entire population into distinct subgroups called strata. The strata are based on a specific characteristic such as age, income, education level, and so on. All members of a stratum share the specific characteristic. Draw random samples from each stratum.
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Stratified Sample
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Number all members of the population sequentially. Then, from a starting point selected at random, include every kth member of the population in the sample.
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Systematic sampling
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