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STA 425 Time Series Analysis

HND2 levelSciences14 topics

STA 425 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. Introduction to time series
  2. Time series components
  3. Moving averages
  4. Trend estimation by moving averages and least squares
  5. Autoregressive models
  6. Parameter estimation and residual analysis for AR models
  7. Serial correlation and autocorrelation
  8. Peaks, troughs and period determination
  9. Fourier analysis
  10. Spectral density
  11. Spectral density in moving average and autoregressive series
  12. Periodogram analysis
  13. Correlogram
  14. Importance of correlograms and spectral analysis

A sample from this course

One topic, as StudyPath teaches it.

Introduction to time series

Introduction to time series covers the definition of a time series, its basic components (trend, seasonality, cyclicity, irregularity), and the importance of stationarity. Mastering these concepts is essential for recognising patterns, selecting appropriate models, and interpreting results in the NUC CCMAS, NBTE, and NCCE exams.

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