A trend is a general direction of change or recurring development in observations over time. In time-series work, identifying it helps distinguish growth from seasonal behavior and informs whether forecasting is worthwhile. section 8.1.2 section 9.4
Investigate a trend through a practical sequence:
- Check the series’ time coverage, granularity, consistency, gaps, missing values, and outliers before interpreting movement. section 8.1.2 section 9.3.1
- Visualize measurements, inspect distributions and individual observations, then look for temporal patterns across locations or periods. section 9.3.1
- Decompose the series to examine trend and seasonality separately, and consider whether past values support forecasting. section 9.3.1 section 9.4
Cycling infrastructure
For cycling data, investigate where traffic is growing, which locations have strong morning activity, and whether available history supports forecasting future cycling trends. Treat the resulting conclusions as one possible analytical path, not an automatic answer. section 8.4 section 9.3.1
