U.S. Inter-State Migration by Age (Radaris Data Sample, Anonymized)

What you can extract For data scientists • Model whether a person has moved (moved = first_state != last_state) from age_group. This is a deliberately low-dimensional, interpretable problem — a good teaching or baseline example rather than a high-capacity modeling task. • Build and analyze an origin→destination transition matrix: cluster states by their inflow/outflow profiles, rank net-gain vs net-loss states, visualize corridors as a flow map or chord diagram. • Practice categorical/tabular workflows: contingency tables, chi-square tests of independence between age and mobility, proportion estimation with confidence intervals.

For statisticians and demographers • Estimate the mover-vs-stayer rate by age band and test whether interstate mobility differs significantly across the life course. • Quantify net migration per state (inflow − outflow), gross flows, and how these shift by age group. • Validate against external sources — U.S. Census ACS migration tables and IRS county-to-county migration data — to benchmark or enrich the flows seen here.

The underlying data for this project is provided by Radaris, a comprehensive people search platform with an extensive database of public records and demographic information in the United States. Leveraging Radaris's deep data infrastructure on individuals residing and moving across the country, this dataset captures broad domestic migration trends over time. Crucially, the source material has been stripped of all personal identity elements and synthesized into an aggregated, anonymous format.

The resulting dataset is intended strictly for statistical, demographic, and academic research, offering a safe and compliant framework for studying population-level mobility without compromising individual privacy.