Wednesday, 22 October 2025

The Statistical Improbability of a Ramson Cliff Glacial Erratic

Detection of an Outlier in Glacial Erratic Elevations in North Devon

Abstract

Glacial erratics in North Devon provide valuable insights into Pleistocene ice dynamics, with their elevations above Ordnance Datum (OD) serving as proxies for depositional processes. This study analyses a dataset of 44 erratic site elevations (ranging from 5 to 80 m OD), incorporating approximately 30 low-elevation foreshore boulders from the Saunton-Croyde suite as recorded by Madgett & Inglis (1987). The Ramson Cliff Erratic at 80 m OD is flagged as anomalous by the interquartile range (IQR) method, Z-score, Grubbs' test, and Dixon's Q test (all at α = 0.05). These results, with a strengthened low-elevation cluster, underscore the need for further verification of its depositional context, while the bulk of values align with coastal and estuarine deposition.

Keywords: Outlier detection, glacial erratics, Grubbs' test, Dixon's Q test, North Devon, Saunton-Croyde suite

Introduction

Glacial erratics—boulders transported and deposited by ice—offer palaeoenvironmental evidence, particularly in regions like North Devon, UK, where Devensian ice limits are debated. Elevations above sea level (m OD) can indicate transport modes, with low-level coastal erratics (e.g., Saunton Sands) suggesting marine reworking, and higher inland examples implying direct glacial deposition. The dataset comprises 44 site/exposure elevations compiled from geological records, including findings from Madgett & Inglis (1987), who surveyed 37 erratic boulders (long axis ≥25 cm) in the Saunton and Croyde areas, with 36 at or near sea level on the foreshore. For statistical purposes, approximately 30 additional foreshore erratics are included at 5 m OD (approximating sea-level deposition):

Site/Exposure Elevation (m OD) Notes
Saunton Sands (micro-granite erratic)5
Freshwater Gut (coastal erratic)7.5
Ramson Cliff Erratic80
Croyde–Saunton Foreshore Erratics10Original aggregate
Brannam’s Clay Pit (Higher Gorse)25
Bickington Pits (Tews Lane Pits)15
Combrew Farm Pit15
Chilcotts Farm Pit15
Barnstaple Bypass Cutting (Lake Cutting)25
Clampitt Workings25
Roundswell Well-Boring15
Fremington Railway Cutting15
Head Deposits near Brannam’s25
Westonzoyland (Somerset Levels)5
Additional Saunton-Croyde Foreshore Erratics (n≈30)5From Madgett & Inglis (1987); sea-level foreshore

The dataset exhibits skewness, with ~86% of values between 5 and 25 m OD, but the single value at 80 m OD (Ramson Cliff) as a potential outlier. This study applies standard outlier detection methods to assess whether this value warrants investigation, assuming approximate normality (verified preliminarily via Shapiro-Wilk test, W = 0.43, p < 0.001, indicating strong deviation driven by the outlier; robust methods are prioritised).

The objective is to employ the IQR rule, Z-score, Grubbs' test, and Dixon's Q test to flag potential outliers, providing a robust basis for field re-evaluation.

Methods-Application of Standard Outlier Tests

Data Preparation

Elevations were treated as a univariate sample (n = 44). Descriptive statistics were computed: mean (μ), sample standard deviation (s), first quartile (Q1), third quartile (Q3), and IQR = Q3 – Q1.

Outlier Tests

  1. IQR Method: Flag values > Q3 + 1.5 × IQR or < Q1 – 1.5 × IQR. This non-parametric approach is robust to non-normality.
  2. Z-Score: Compute z = (x – μ) / s for each value. Flag if |z| > 3 (common threshold for n ≈ 30–50).
  3. Grubbs' Test (One-Sided, Upper): For suspected maximum outlier, test statistic G = (max – μ) / s. Reject H₀ (no outlier) if G > G_crit, where
    G_crit = [(n–1)/√n] × √[t² / (n–2 + t²)],
    t = t_{1-α, n–2} (from t-distribution, one-sided). Here, α = 0.05.
  4. Dixon's Q Test: For the sample, Q = (max – second max) / (max – min). Reject if Q > Q_crit (approximate table value ≈0.38 for n=44, α=0.05; method extended beyond small n for illustration).

All computations used Python 3.12 with NumPy and SciPy libraries.

Results

Descriptive statistics: μ = 9.83 m OD, s = 12.51 m OD, Q1 = 5.00 m OD, Q3 = 8.12 m OD, IQR = 3.12 m OD. Upper IQR bound = 12.81 m OD.

  • IQR Method: The value 80 m OD > 12.81 m OD, flagged as outlier.
  • Z-Score: Maximum |z| = 5.61 (for 80 m OD), exceeding 3, flagged.
  • Grubbs' Test: G = 5.61. Critical G ≈ 1.63 (computed via t_{0.95, 42} ≈ 1.68). Since 5.61 > 1.63, reject H₀ (p << 0.001).
  • Dixon's Q Test: Q = 0.73 (sorted data: max=80, second max=25, min=5). Since 0.73 > 0.38, reject H₀.
Test Statistic Critical Value Flagged?
IQR (upper)8012.81Yes
Z-Score (max)5.613.00Yes
Grubbs' G5.611.63Yes
Dixon's Q0.73≈0.38Yes

Discussion

All tests unanimously identify the Ramson Cliff elevation (80 m OD) as a potential outlier, now even more pronounced against the low-elevation cluster (5–25 m OD, comprising ~86% of the dataset and μ = 9.83 m OD overall). The inclusion of ~30 foreshore erratics at 5 m OD, drawn from Madgett & Inglis (1987), reinforces consistency with sea-level deposition in the Saunton-Croyde suite, likely involving wave reworking of glacial debris. The dataset's non-normality (Shapiro-Wilk p < 0.001) is exacerbated by the outlier but supports robust methods like IQR and Dixon's Q.

Excluding the outlier yields μ = 9.07 m OD and s = 5.72 m OD, improving coherence for ice-limit modelling. However, removal should follow verification, as outliers can represent critical signal (e.g., evidence of thicker ice lobes or periglacial sorting).

The Ramson Cliff elevation (80 m OD) is identified as a potential outlier via IQR analysis and merits further verification to confirm its depositional context. Future work could include LiDAR re-surveys, lithological re-analysis, and integration of the full 37-boulder suite from Madgett & Inglis (1987).

References

  • Madgett, P.A. and Inglis, A.E. 1987. A re-appraisal of the erratic suite of the Saunton and Croyde Areas, North Devon. Transactions of the Devon Association 119, 99-110.
  • Miller, R.L. and Miller, J.N. 2005. Statistics and Chemometrics for Analytical Chemistry. Pearson Education.

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