Unemployment Crime Correlation Calculator

Actual independently harmonized known regional-period correlation, composing existing Pearson calculation and retaining unresolved IDs. Correlation does not establish causation or individual criminality.

Description

Correlation describes linear association among matched region-period observations.

Correlation describes linear association among matched region-period observations.^[1]

It does not establish that unemployment caused the recorded crime pattern. Use this tool to calculate the stated observation or conditional model from supplied measurements.

When to use Unemployment Crime Correlation Calculator

Use this tool to calculate the stated observation or conditional model from supplied measurements. Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.

How to use Unemployment Crime Correlation Calculator and understand its results

Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.
Enter callerRegionPeriodIds, independentlyMatchedUnemploymentMeasures, independentlyMatchedRecordedCrimeMeasures, pairedKnownFlags, using the field meanings and rules below, then run the tool.
Read result.observedKnownCorrelation, result.includedCallerIds, result.unknownCallerIds. Interpret each field using the units, signs and evidence rules below.
If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.

Input field	Meaning	Value type	Requirement
callerRegionPeriodIds	Caller region period ids	list of string	Required
independentlyMatchedUnemploymentMeasures	Independently matched unemployment measures	list of number	Required
independentlyMatchedRecordedCrimeMeasures	Independently matched recorded crime measures	list of number	Required
pairedKnownFlags	Paired known flags; 1 means known and 0 means unknown; keep the same item order	list of number	Required

Supply nonempty unique nonblank region-period IDs with aligned finite unemployment/crime measures and binary paired-known flags. Filter both series to the known pairs. Require at least two known pairs with nonzero variation in both series; compute centered Pearson correlation and round it to 15 significant digits. Return included and unknown IDs in caller order. No lag choice, covariate adjustment or causal estimate is supplied.^[2]

r=Σ((x_i−meanX)(y_i−meanY))/sqrt(Σ(x_i−meanX)²×Σ(y_i−meanY)²), over known pairs

Apply the field units and exact ordering, boundary and evidence rules above.

Output field	Meaning	Value type
result	Structured result containing the calculation or selected reference fields below	object
result.observedKnownCorrelation	Observed Known Correlation; use the units, sign convention and calculation stated above	number
result.includedCallerIds	Included Caller Ids; use the units, sign convention and calculation stated above	list of string
result.unknownCallerIds	Unknown Caller Ids; use the units, sign convention and calculation stated above	list of values

json

{
  "input": {
    "callerRegionPeriodIds": [
      "a",
      "b",
      "c"
    ],
    "independentlyMatchedUnemploymentMeasures": [
      1,
      2,
      3
    ],
    "independentlyMatchedRecordedCrimeMeasures": [
      3,
      2,
      1
    ],
    "pairedKnownFlags": [
      1,
      1,
      1
    ]
  },
  "output": {
    "result": {
      "observedKnownCorrelation": -1,
      "includedCallerIds": [
        "a",
        "b",
        "c"
      ],
      "unknownCallerIds": []
    }
  }
}

Limitations and assumptions

It does not establish that unemployment caused the recorded crime pattern. Results depend on the independently established measurement basis and the exact model assumptions above.

Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.

Alternative or Complementary methods

Use Lead Exposure Crime Lag Decades Reference Lookup to examine a related aspect: Lead-exposure and crime-lag studies compare populations under particular research designs.

Use Crime Trend Percent Change YoY Calculator where its separate inputs and scope apply: Year-on-year percent change compares recorded counts on a matched basis.

References

Unemployment Crime Correlation Calculator — tool.io
Implementation helper: statistics/pearson-correlation — tool.io

Similar or alternative tools

Lead Exposure Crime Lag Decades Reference Lookup
Lead-exposure and crime-lag studies compare populations under particular research designs.
Crime Trend Percent Change YoY Calculator
Year-on-year percent change compares recorded counts on a matched basis.