Introduction to Statistical Inference

  • Bryan Kestenbaum

Learning Objectives

  1. 1.

    A sample is a subset of individuals derived from a given population.

  2. 2.

    Statistical inference relates findings from a sample to those in the population.

  3. 3.

    Generalizability refers to the scientific/practical relevance of the underlying population.

  4. 4.
    Factors that increase the likelihood that sample findings reflect those of the population:
    1. a.

      Large sample size

    2. b.

      Small population variation

  5. 5.
    95% confidence intervals:
    1. (a)

      If a study is repeated indefinitely and a 95% confidence interval placed around each sample mean, then 95% of the intervals will contain the true population mean.

    2. (b)

      Can be calculated without knowing the true population mean.

    3. (c)

      Will be narrower when the sample size is large and the sample variation is small.

  6. 6.
    1. (a)

      Given a null hypothesis regarding the population, the p-value is the probability of observing the sample result, or a more extreme result, due to sampling variation.

    2. (b)

      Findings from a particular sample are used to make an inference about the true results in the population.



Relative Risk Statistical Inference Sample Result American Adult True Association 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.University of WashingtonSeattleUSA

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