Question

explain the difference between effect size and confidence interval.

explain the difference between effect size and confidence interval.

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Answer #1

Effect size

  • Effect size is a statistical concept that measures the strength of the relationship between two variables on a numeric scale.
  • Statistic effect size helps us in determining if the difference is real or if it is due to a change of factors.
  • the effect size is usually measured in three ways: (1) standardized mean difference, (2) odd ratio, (3) correlation coefficient.

Confidence interval

  • confidence interval, in statistics, refers to the probability that a population parameter will fall between two set values for a certain proportion of times. Confidence intervals measure the degree of uncertainty or certainty in a sampling method.
  • A confidence interval can take any number of probabilities, with the most common being a 95% or 99% confidence level.
  • Statisticians use confidence intervals to measure uncertainty.
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