Time Series Analysis · Statistics
Very good course the combines theory and data. Wish there was slightly more focus on the math (maybe optional hw tracks or a different project for students who prefer math over data?) e.g. we did not talk about spectral methods of time series analysis
I learned basic time series models. got an overview of how to build a time series model using R.
Comprehensive knowledge about time series
Different TS models and concepts in theory and mathematic formulas and how to determine what model is acceptable
Time series models: AR/MA/ARMA/ARIMA and its application.
It depends on how relevant ARMA models will be for your future field
Turn on the camera, engage more with students. We are not robots!
Least squares smoothing and prediction, linear systems, Fourier analysis, and spectral estimation. Impulse response and transfer function. Fourier series, the fast Fourier transform, autocorrelation function, and spectral density. Univariate Box-Jenkins modeling and forecasting. Emphasis on applications. Examples from the physical sciences, social sciences, and business. Computing is an integral part of the course.
Basic concept of time series; ARMA model estimation and prediction
AR MA process, ACVF, ACF, forecasting, spatial density