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Statistics By Jim

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Sample

By Jim Frost

A sample is a subset of the entire population. In inferential statistics, the goal is to use the sample to learn about the population. Consequently, the sample typically is selected in a manner that allows it to be an unbiased representation of the entire population. Drawing a random sample is a common method for achieving this unbiased representation. In a simple random sample, each member of the population has an equal probability of being included in the sample. However, different modifications of simple random samples can be used to meet specific research needs.

Related

Related Articles:
  • Simple Random Sampling
  • Systematic Sampling
  • Stratified Sampling
  • Cluster Sampling
  • How to Interpret P-values and Coefficients in Regression Analysis
  • How Hypothesis Tests Work: Significance Levels (Alpha) and P values
  • How To Interpret R-squared in Regression Analysis
  • Interpreting P values
  • How to Identify the Distribution of Your Data

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    Top Posts

    • How to Interpret P-values and Coefficients in Regression Analysis
    • How To Interpret R-squared in Regression Analysis
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    • How to Interpret the F-test of Overall Significance in Regression Analysis
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