48 Experiments

An ongoing program of computational research testing astrological hypotheses against empirical data — with full transparency on methodology and outcomes, including null results. Published in peer-reviewed journals and presented at academic conferences.

A scientist who studies astrology

Renay Oshop's research program asks a deceptively simple question: does astrology actually predict anything? Not with anecdote or client testimonials — but with data, control groups, effect sizes, and statistical inference.

The 48 experiments span a wide range of astrological hypotheses — from birth chart correlates with wealth and personality, to market volatility, weather, career patterns, genetic traits, and the performance of mundane predictions. The methodology is drawn from computational biology and data science. The results are reported honestly.

Some experiments return positive results. Some return null. Some are mixed. All are published. This is what distinguishes rigorous inquiry from advocacy — and it is what gives the positive results their weight.

Full details at bigastrologybook.com ↗

The 48 projects

Outcomes: Positive — Statistically significant result supporting hypothesis Null — No significant effect found Mixed — Partial or inconsistent support Incomplete — Design ready; data collection pending Low — Below threshold significance
Filter:
# Project / Keywords Outcome Key Finding
01Births / Wealth — correlation between birth chart factors and economic outcomesMixedNo statistical significance; large effect sizes worth pursuing
02Economic Cycles — planetary cycles and macro-economic indicatorsMixedr=0.0226 — real but tiny; not predictive
03Hospital / Moon — lunar phase and hospital admissions / emergency room visitsNullFull Moon Effect definitively refuted at 156M births
04Gauquelin Replication — geographic / Mars effect and athletic achievementPositiveUrbanization r=0.719; astrology = urban/educated
05Retrograde / Bias — retrograde planets and cognitive or behavioral biasNullNo effect after detrending; calendar confounds explain all
06Aspects / Harmonics — harmonic aspect patterns and personality measuresPositiveH4/H7 elevated in achievers; selective positive
07Machine Learning / Personality — ML models predicting personality from natal dataMixedProfession classification 29.3% vs 16.7% baseline
08Precession — tropical vs. sidereal zodiac performance in predictionsNullSun Sign worse than random in all systems
09Solar / Quality — solar position and quality-of-life self-report measuresIncompleteDesign presented; mood dataset needed
10Synastry / Longevity — chart compatibility and relationship durationMixedMars-Mars p=0.0006 genuine signal
11Health / Cohort — natal indicators and health outcomes in cohort datasetsNullSun sign p=0.964; no longevity signal
12Market / Volatility — planetary configurations and stock market volatilityNullPlanets worsen GARCH forecasts
13Circular Statistics — methodological study of circular/angular data in astrologyNullNo zodiac clustering by profession
14Ancient Mechanics — testing classical Jyotisha rules against modern datasetsMixedScientists: debilitated Tropical, dignified Sidereal p=0.042
15Birth Order — astrological indicators and sibling birth order effectsMixedFirstborn Fire signs elevated; Saturn shift = astronomical fact
16Creativity / Generations — generational patterns and creative output metricsNullNeptune aspects lower in geniuses than random; powered null
17Transits / Predictions — predictive accuracy of transit-based forecastsPositive★ +148% cosine sum on event days p<0.0001 — strongest result
18House Systems — comparative performance of tropical vs. whole-sign housesPositive31.8% hit rate vs 25% baseline; BF=23.5
19Mundane / Events — chart-based predictions for geopolitical or world eventsIncompleteBase rate problem: outer aspects active ~48% of time
20Genetic / Rules — classical astrological rules and genetic outcome dataPositiveMars in Libra 18.6%; Moon in Scorpio 17.4% — Hardship Hypothesis
21Eclipse / Mood — solar/lunar eclipses and population-level mood measuresNullNo elevation on eclipse days
22Astro / Weather — planetary indicators and meteorological outcomesMixedWater Sign/rain = seasonal artifact; syzygy dip marginal
23Career / Similarity — chart patterns shared among people in the same careerPositiveVedic within-career clustering p<0.001
24Electional / Decisions — electional astrology and decision outcome qualityNullAll three electional rules: <0.2% return difference
25Fixed Stars — fixed star parans and biographical correlatesPositiveRegulus/Altair Z-score findings (descriptive)
26Compatibility — synastry indicators and reported relationship satisfactionNullr=0.009; survival curves overlap perfectly
27Horary — accuracy of horary astrology answers vs. outcomesIncompleteFramework ready; data needed
28House / Life Domains — house placements and corresponding life domain outcomesPositivePoliticians peak at 1st Solar House +166%
29Asteroids / Psychology — minor planet positions and psychological measuresPositivePallas/Juno/Vesta solar conjunctions elevated
30Culture / Zodiac — cross-cultural comparisons of zodiac trait associationsIncompleteAll traits p<0.001 but η²≈0.002; generational confound
31Disease / Pattern — astrological indicators in disease onset pattern studiesIncompleteSaturn-Uranus p=0.0021; none survive Bonferroni
32History / Predictions — retrospective accuracy of historically documented predictionsNull56.4% accuracy p=0.26; electional worst at 25%
33Dignities / Character — planetary dignities and character trait correlationsPositiveWriters: weak Mars p=0.011; Filmmakers: strong Sun p=0.027
34Solar Returns — solar return chart accuracy for annual life themesMixedMoon-Lilith at Death p=0.009; Venus-Uranus at Marriage p=0.016
35Professional Clustering — unsupervised ML on birth charts by profession (N=766)NullARI ≈ 0 across six algorithms; no vocational structure in chart space
36Synastry Harmonics — logistic regression on relationship longevity (N=4,000 couples, 700+ features)NullML lift traced to birth cohort (~1905 era), not astrology; ROC-AUC = 0.5
37Planetary Cycles & Mood — long-term planetary cycles and consumer sentiment index (N=668 months)MixedMercury Rx null (p=0.896); Jupiter-Saturn cycle r=−0.19 (p<0.0001) confirmed
38Composite Charts — angular cohesion and musical group longevity (N=31 bands)MixedMoon Cohesion r=+0.25 promising but underpowered; needs N≥190
39Retrograde & Markets — planetary retrograde periods and VIX volatility (75 years of data)MixedMercury Rx myth dead; Venus Rx +10% VIX confirmed over 75 years (p<0.0001)
40Medical Astrology — decumbiture and illness severity (82M NYC ED visits, 1,008 days)MixedOuter planet r=0.49 = generational artifacts; Sun-Saturn & Mars-Saturn genuine; Moon null
41Lunar Nodes & Life Purpose — North Node placement and professional category (N=763)LowArchetypal trends correct direction (Entertainers 5th house, Politicians 10th); underpowered
42Solar Cycles & Sentiment — sunspot cycles and collective consumer mood (1960–2023, N=624)Mixedr=−0.193 real over 64 years; 2016-2023 r=−0.74 was spurious phase-alignment
43Progressions & Development — secondary progressions and life event type (N=171 charts, 925 events)MixedHard aspects inverted — positive events have more; Mars/Venus ingresses & Progressed Moon genuine
44ML Rectification — machine learning to reverse-engineer birth time from life events (N=5,000 synthetic)PositiveCosine features cut birth time error 54% (MAE 6h → 2.7h); raw coordinates failed
45Seismicity & Gravity — lunar cycles and earthquake frequency (N=25,961 quakes M5.5+)MixedLunar day χ²=78.54 (p<0.0001) confirmed but inverted — New Moon suppresses, Crescent peaks
46NLP & Archetypes — thematic coherence of astrological sign descriptions (N=10,000 readings)PositiveSame-element similarity 0.65–0.72; LDA recovers four elements unsupervised
47Moon Phase & Sleep — lunar phase and wearable sleep quality (~118,000 user-nights)PositiveFull Moon cuts deep sleep 15.5 min (~20%, p<0.00001); melatonin light-exposure mechanism
48Genetic Algorithms — evolutionary feature selection across financial, market, and natal datasetsMixedVIX: R²=+0.058; IPO returns: R²=+0.114 (+14% vs naive); daily returns: null; 6 sub-experiments

Methodology philosophy

The research program is built on principles drawn from empirical science. These are not incidental — they are what separates genuine inquiry from motivated reasoning.

Falsifiability

Every experiment starts with a hypothesis that can, in principle, be disproved. If no possible outcome could count as evidence against a claim, the claim is not scientific. Renay's experiments are designed to be losable — and some of them have been lost.

Control Groups

Where possible, astrological test groups are compared against matched control groups drawn from the same population. Effect sizes are calculated against baseline rates, not just internal patterns. This prevents confirmation bias from skewing interpretation.

Transparent Reporting

Null results are published alongside positive ones. This is unusual in the astrological literature — and essential for credibility. A research program that only publishes hits tells you nothing. Publishing misses is what gives the hits their evidential weight.

Statistical Rigor

Results are evaluated using standard statistical methods — chi-square, effect size, significance thresholds, confidence intervals. The goal is not impressive numbers but reproducible methods that other researchers can audit and attempt to replicate.

Large Datasets

Where feasible, experiments use large naturalistic datasets — public records, news corpora, financial data — rather than small laboratory samples. This increases statistical power and reduces the risk of idiosyncratic findings.

Epistemic Humility

The research does not prove astrology universally true or false. It provides evidence about specific hypotheses. Some astrological claims appear to have measurable correlates. Others don't. That distinction matters — and it is honored.

Selected Bibliography

Peer-reviewed papers, journal articles, conference presentations, podcast appearances, and other para-published materials from Renay's research on Ayurveda and Astrology.

  1. The Big Astrology Book of Research More than fifty contemporary experiments in computational astrology — with data, code, images, and text. bigastrologybook.com. January 2026.
  2. Truth Alone Wins. A conversation with Alex Gil on the Rebranding God podcast series. Available on Spotify, Google, Apple Podcasts. May 25, 2023.
  3. How machine learning addressed an ancient claim: Descriptions of 7,152 mundane events correlate with celestial positions. Correlation, 34(2) 2022, pp. 35–41.
  4. Across Millions of Pairs, Text Similarities in Descriptions of Events Likely Depend on Similarities in Astrology Charts. SSE-PA Breakthrough 2022, Society for Scientific Exploration and Parapsychological Association Joint Conference, Jun 24, 2022. Proceedings.
  5. Numbers of News Articles Names of Minor Planets Reflect Their Degree Differences from the Sun. I-Astrologer Conference, Organization of Professional Astrologers, May 13, 2022.
  6. Bhutonmad: Ayurveda of Space, Time, Karma and Guna of a Shooting (As Seen Ahead of Time). Presented to Colorado Ayurvedic Medical Association. January 2020.
  7. Astronomy of the day is more effective than seasonal decomposition in modeling and predicting the rates of Amazon review misspellings. International Journal of Scientific Research and Management, Feb 2019, Vol. 7, No. 2. DOI: 10.18535/ijsrm/v7i2.aa01.
  8. Easy Machine Learning Using Astrology. Syzygy, Vol. 8, Winter 2018–2019, pp. 12–15. Also published at Instructables.com (July 2018).
  9. Renay Oshop on Astrological Research and a Scientific Approach to Astrology. YouTube. November 13, 2017.
  10. Renay Oshop, Peer Reviewed Science Comes to Astrology. Skeptiko.com audio interview. April 2017.
  11. Astronomical Factors at Birth Correlate to Online Personality Self-Assessment and Can Be Useful in Its Classification. The Kepler Conference, Cape Canaveral, FL. January 2017.
  12. Mercury Retrograde Correlates with Amazon Review Misspellings, Helping to Build a More Accurate Misspellings Predictor Using Only Astronomy. The Kepler Conference, Cape Canaveral, FL. January 2017.
  13. Astrology, the Queen of All the Pseudo-Sciences. Presented at Society for Scientific Exploration Conference, Boulder, CO. 2016.
  14. Twitter Followers Biased to Astrological Charts of Celebrities. Journal of Scientific Exploration, Vol. 29, No. 1, pp. 9–34. 2015.
  15. Troubling Benefic: Jupiter in Diabetes Type One. CVA Journal, Spring/Summer 2009, p. 27.
  16. Numerology and the Solstice. Michael Laughrin's North American Jyotish Newsletter. December 2008 / January 2009.
  17. A Cystic Fibrosis Case Study Yields Clues to Ayurvedic Pathogenesis and Treatment. Light on Ayurveda Journal of Health, Fall 2008, Vol. 7, Issue 1, p. 32.
  18. Diabetes and Astrology Part One: A Simple Astrological Marker for Type 1 Diabetes. Michael Laughrin's North American Jyotish Newsletter. August / September 2008.

Read the full research

The Big Astrology Book of Research is the primary publication for this work — with full experiment descriptions, datasets, and extended analysis available at bigastrologybook.com.

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