STAT 560 Time Series Analysis

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This STAT 560 Time Series Analysis course covers the topics of time series analysis and statistical forecasting techniques. These are time series regression, decomposition methods, exponential smoothing, and Box-Jenkins prediction methods.

The main goal of this STAT 560 Time Series Analysis course is to introduce graduate and undergraduate students in mathematics, economics, business, engineering and any other field where time series analysis is important, some of the many methods of analyzing time-series data. In addition, we will equip them with the tools and knowledge to make predictions through statistical analysis of historical data.

Time series analysis is a statistical technique for processing time-series data or analyzing trends. It is believed that there are three types of data:

• Time series data: A set of observations of the value of a variable at different times
• Lateral data: Data from one or more variables collected at the same point in time.
• Consolidated data: A combination of time series data and cross-sectional data.

Student learning outcomes:

• Use a variety of statistical techniques to analyze time-series data
• Make smart predictions

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