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BIOSTAT645 Time Series Analysis with Biomedical Applications

  • Fall term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Johnson, Timothy
  • Not offered 2013-2014
  • Prerequisites: Biostat 602, Biostat 650 or Perm. Instr
  • Description: Introduction to statistical time series analysis with an emphasis on frequency domain (spectral) methods and their applications to biomedical problems. Topics include autocorrelation, stationarity, autoregressive and moving average processes, power spectra, periodgrams, spectral estimation, linear filters, complex demodulation, autoregressive integrated moving average (ARIMA) models, cross-correlation, cross-spectra, coherence, time and frequency domain linear regression. The methods will be illustrated in applications to various areas of public health and medical research such as environmental health, electrophysiology, and endocrinology.
  • Syllabus for BIOSTAT645 (PDF, 23694 bytes, last modified on Tuesday, February 21, 2012)

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