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STA 424 Statistical Computing

HND2 levelSciences14 topics

STA 424 covers 14 topics. StudyPath paces them into daily study sessions that finish before your exam date, with practice questions and worked answers for each one.

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Course outline

The topics this course covers, in teaching order.

  1. Random numbers and pseudo-random numbers
  2. Methods of random number generation
  3. Random number generators
  4. Random variates from standard distributions
  5. Tests of randomness and independence
  6. Numerical solution of equations
  7. Root-finding methods
  8. Numerical matrix methods
  9. Eigenvalues, eigenvectors and matrix inverse
  10. Kernel density estimation
  11. Smoothing parameter and kernel functions
  12. Flowcharts and statistical algorithms
  13. Algorithms for random sampling and test procedures
  14. Randomness tests and multiway tables

A sample from this course

One topic, as StudyPath teaches it.

Random numbers and pseudo-random numbers

Random numbers are values that cannot be predicted in advance and are used to model uncertainty in statistical simulations. Pseudo‑random numbers are deterministic sequences that mimic randomness and are generated by algorithms; they are essential for reproducible Monte‑Carlo studies, bootstrapping, and random sampling in the sciences.

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