Statistics: A Review

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A one-day, intensive review of common statistical methods of design, measurement analysis and presentation of scientific investigations.  The workshop is designed for any scholar engaged in quantitative research. Statistics: A Review discusses answers to the following questions:

  • What should we measure?
  • What are the main design types; what are the comparative advantages of each?
  • How are the sample sizes determined?
  • What are the appropriate inference procedures?
  • What do standard error, p-value and confidence level mean?
  • What are some dangers we need to avoid?
  • How should we display our results?
  • What are the statistical software options?

 

Biostatistics Seminar: Kenneth Lange, Professor of Biomathematics, Human Genetics and Statistics, UCLA: “Next Generation Statistical Genetics”

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This talk will discuss how modern data mining techniques can be imported into statistical genetics. Most relevant models now invoke high-dimensional optimization. Penalization and set projection give sparsity. Separation of variables gives parallelization. Time permitting, these ideas will be illustrated by several examples: estimation of ethnic ancestry, genotype imputation via matrix completion, conversion of imputed genotypes into haplotypes, matrix completion discriminant analysis, estimation in the linear mixed model, iterative hard thresholding in GWAS, and sparse principal components analysis.