Central limit theorem - Normal Distribution and Z-Scores

Central limit theorem


The distribution of sampling means is normally distributed
\cdot μx=μ\mu_{\overline{x}}=\mu
\cdot σx=σn\sigma_{\overline{x}}=\frac{\sigma}{\sqrt{n}}

Central Limit Theorem:
Typically n30n \geq 30
  • Intro Lesson
  • 1.
    Comparing the Individual Z-Score to the Central Limit Theorem
    A population of cars has an average weight of 1350kg with a standard deviation of 200 kg. Assume that these weights are normally distributed.
  • 3.
    Increasing Sample Size
    At the University of British Columbia the average grade for the course “Mathematical Proofs” is 68%. This grade has a standard deviation of 15%.
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Central limit theorem

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