FeaturedUdemy
Time Series Analysis in R
4.9(89)61k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate course delivers essential statistical techniques for modeling time-dependent data in R. Learners explore foundational time series concepts, diagnostic tools, and forecasting routines to evaluate fluctuating data streams such as stock market movements.
Who It's For
R users and quantitative analysts who want a solid foundation in time series manipulation, visualization, and modeling.
Key Takeaways
- Core Concepts: Understand unique properties of time series data structures and regular interval measurements.
- Exploratory Tools: Learn methods to decompose time series into trend, seasonal, and residual components.
- Statistical Modeling: Apply core R time series techniques to analyze historical patterns and forecast outcomes.
About this course
Many phenomena in our day-to-day lives, such as the movement of stock prices, are measured in intervals over a period of time. Time series analysis methods are extremely useful for analyzing these special data types. In this course, you will be introduced to some core time series analysis concepts and techniques.
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