datareeksen

Datareeksen, literally “data series” in Dutch, is a sequence of data points ordered in time or by another index. In statistics and data science, a datareeksen refers to data collected in a row where each observation has a position in the sequence. When the index corresponds to time, it is commonly called a time series. Datareeksen can be univariate (one variable) or multivariate (multiple variables observed at each time point).

Structure and terminology: Observations are paired with an index, such as a timestamp. Frequency may be regular (hourly, daily) or irregular. Key properties include trend, seasonality, cyclic patterns, and irregular noise. Data quality issues include missing values and outliers, which require imputation or robust methods.

Collection and preprocessing: data may come from sensors, logs, surveys. Preprocessing steps include alignment, resampling to a common frequency, missing data handling, normalization, and smoothing.

Analysis and applications: common methods include descriptive statistics, decomposition, smoothing, ARIMA, exponential smoothing, state-space models, and machine learning approaches for forecasting. Applications span finance, economics, meteorology, engineering, and web analytics. Panel data or longitudinal data refers to datareeksen observed for multiple units over time, combining cross-sectional and temporal dimensions for richer analysis.