Central Limit Theorem and Confidence Intervals Quiz
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Questions and Answers

Which theorem is critical to note if the distribution is non-normal and the sample size is low?

  • Law of Large Numbers
  • Central Limit Theorem (correct)
  • Chebyshev's Inequality
  • Bayes' Theorem
  • What is the requirement for the Central Limit Theorem to apply?

  • Non-normal distribution or sample size above 30
  • Normally distributed population and sample size above 30
  • Normally distributed population or sample size above 30 (correct)
  • Non-normal distribution and sample size above 30
  • Which distribution is similar to the normal distribution and can be thought of as its 'brother'?

  • Z distribution
  • T distribution (correct)
  • Poisson distribution
  • Binomial distribution
  • What is the purpose of using the T distribution instead of the Z distribution?

    <p>To account for small sample sizes</p> Signup and view all the answers

    Which theorem is used to construct confidence intervals?

    <p>Central Limit Theorem</p> Signup and view all the answers

    Study Notes

    Non-Normal Distributions and Small Sample Sizes

    • The Tchebysheff Theorem is critical to note if the distribution is non-normal and the sample size is low.

    Central Limit Theorem

    • The requirement for the Central Limit Theorem to apply is that the sample size must be sufficiently large.

    Normal Distribution Relatives

    • The Logistic Distribution is similar to the normal distribution and can be thought of as its 'brother'.

    T and Z Distributions

    • The T distribution is used instead of the Z distribution when the population standard deviation is unknown and the sample size is small.
    • The T distribution is more conservative and has a larger variance than the Z distribution.

    Confidence Intervals

    • The Central Limit Theorem is used to construct confidence intervals.

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    Description

    Test your understanding of the Central Limit Theorem and its application in constructing confidence intervals. Explore the conditions for the theorem to hold and learn when to use Z or T statistics.

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