- Implementing Computational Statistics Methods (k4)
Students can implement key computational statistics techniques such as non-linear optimization, root finding, and the EM algorithm to analyze statistical problems effectively.
- Generating and Applying Pseudorandom Numbers (k3)
Students are able to use algorithms for pseudorandom number generation and apply these numbers in statistical simulations and analyses.
- Applying Numerical Methods (k4)
Students can use numerical integration techniques and employ methods like Jackknife and bootstrap for statistical precision and variance estimation.
- Performing Permutation Tests and Regression Analysis (k5)
Students are capable of performing permutation tests to evaluate hypotheses and conducting regression analyses to understand relationships within data.
- Ensuring Accuracy in Statistical Computation (k5)
Students can evaluate the precision of statistical computations, understanding the implications of computer arithmetic on results and ensuring the reliability of their statistical analysis.
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Students have theoretical understanding of computational statistics principles, including the EM algorithm, numerical integration, and methods to assess statistical accuracy like the Jackknife and bootstrap. They are also familiar with pseudorandom number generation, non-linear optimization, root finding, permutation tests, and regression analysis, enabling the practical application of these methods to real-world data problems.
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