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Minimum Statistics Requirements for MSCA 602: Applied Linear Statistical Models

Description Statistics

  • Description summary measure from a sample: center and spread of distribution, quantiles.
  • Data presentation: stem-and-leaf display, box-and-whisker plot, histograms and dot plots.


  • Basic properties and rules: addition and multiplication rules; conditional probability; independence.

Random Variables

  • Definition and properties of discrete and continuous random variables; the expected value (mean) and variance of a random variable.
  • Normal distribution: properties of the normal distribution; standard normal variable.

Sampling Distribution

  • Measure of a sampling distribution; standard error.
  • Normal approximation to sampling distributions (central limit theorem in the case of a sample mean).

Statistical Inference

  • Statistical estimation
    • The meanings of point and interval estimation. The cases of a single mean and the difference of two means from independent samples.
    • The T distribution
    • The F distribution.
  • Hypothesis testing
    • Hypothesis testing procedure;
    • Type I and type II errors;
    • The p-value of a test;
    • Relations between tests and confidence intervals;
    • Chi-square goodness-of-fit test for probability distributions.
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