fintech-algorithms
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Sampling, Estimation, and Statistical Inference

10 algorithms in Financial Mathematics, Statistics, and Data Foundations · 10 with asserted arithmetic.

In this family#

  1. Parameters, Statistics, Estimands, and Estimators verified

    parametersStatisticsEstimandsAndEstimators(input)
  2. Sampling Distributions verified

    samplingDistributions(input)
  3. Estimator Bias, Consistency, Efficiency, and Robustness verified

    estimatorBiasConsistencyEfficiencyAndRobustness(input)
  4. Law of Large Numbers verified

    lawOfLargeNumbers(input)
  5. Central Limit Theorem verified

    centralLimitTheorem(input)
  6. Standard Error verified

    standardError(input)
  7. Confidence Intervals and Coverage verified

    confidenceIntervalsAndCoverage(input)
  8. Null and Alternative Hypotheses verified

    nullAndAlternativeHypotheses(input)
  9. P-Values, Significance, Type I/II Errors, and Power verified

    pValuesSignificanceTypeIIiErrorsAndPower(input)
  10. Effect Size, Practical Significance, and Multiple Comparisons verified

    effectSizePracticalSignificanceAndMultipleComparisons(input)

What they share#

Every topic here is a record-transform, so once you have called one the rest follow the same shape. Import paths differ only in the final segment:

ts
import { parametersStatisticsEstimandsAndEstimators } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/sampling-estimation-and-statistical-inference/parameters-statistics-estimands-and-estimators";
import { samplingDistributions } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/sampling-estimation-and-statistical-inference/sampling-distributions";

Read them in the order above — the sequence is pedagogical, not alphabetical.

Where this sits#

Financial Mathematics, Statistics, and Data Foundations collects 120 algorithms across 12 families. For the concept behind this family rather than the call signatures, see the concept guides.