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The short training will consider how and where to get environmental and ecological data and using R Statistical Software to carry out analysis.
Join us for hands-on session on analyzing data collected over time.

Why R? R handles trends, yearly cycles, anomalies, and forecasting properly using `ts`, `forecast`, and `fable` packages.

What you’ll do:

  1. Clean messy dates and plot seasonal patterns
  2. Decompose data into trend + seasonal + remainder
  3. Fit ARIMA models and forecast next 12 months with confidence bands
  4. Detect anomalies — was January 2024 flood a statistical outlier?

Kwara-Environmental-Statistics-R members working with weather stations, ecological surveys, pollution monitors, or crop records and students. You know `ggplot2`. Never touched time series? We start from `read.csv`.

Related topics

Events in Ijagbo
Data Science
Data Visualization
Ecology
Environmental Awareness
Applied Statistics

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