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Statistics 2026-06-13

Lyon 3 Business Law Portfolio Analysis

Evaluate your admission probabilities across all 12 Business Law master's tracks at Université Jean Moulin Lyon 3 using a probabilistic model.

Generated by: Claude 3.5 Sonnet
Copy and paste this prompt in the AI

Using only the MonMaster MCP — no web search, no external rankings — analyse the following formation(s): all Droit des affaires formations at Université Jean Moulin Lyon 3 (search by city Lyon, mention Droit des affaires, establishment Lyon 3) For each formation, retrieve: candidatures confirmées (N), capacité (C), rang du dernier appelé (R), and taux d'accès (A). Then compute and report the following derived metrics: 1. Demand intensity → N / C (applicants per seat) 2. Admission bar → R (absolute rank of last admitted) 3. Yield proxy → C / R (share of offers that convert; low = popular first-choice) 4. Selectivity signal → A = R/N (verify mechanically against raw figures) 5. Offer inflation → R / C (offers made per seat; high = waitlist moves far) Interpret each metric in plain language. Flag any statistical artefact (e.g. micro-cohort distortions, dual M1/M2 entries, apprentissage splits inflating or deflating A%). Produce a probabilistic tiering for a candidate whose likely pool percentile is [[µ — e.g. "top 7%"]] with evaluation noise σ = 4 points, using the formula P(admit) = Φ((A − µ) / σ). Label each programme: HIGH REACH (<15%) · REACH (15–40%) · MATCH (40–80%) · SAFETY (>80%) Run a sensitivity check: recompute P at µ − 3pp and µ + 3pp and state how the tier label changes. Format the output as: • A ranked table (N, C, R, A%, N/C, R/C, yield%, P%, tier) • A prose interpretation of the 2–3 most statistically significant findings • An interactive visual: scatter plot of N (x-axis, demand) vs A% (y-axis, selectivity, inverted) with bubble size = C, colour = tier, and hover tooltips showing all metrics • A reach/match/safety tiering card per programme Do not use any data source other than MonMaster MCP tool calls. After completing the standard analysis above, compute the joint probability of receiving at least one offer at MATCH tier or above across the full portfolio, assuming independent admission decisions: P(≥1 match) = 1 − ∏(1 − Pᵢ) for all programmes where tier ∈ {MATCH, SAFETY} Present this as a single summary statistic and state which 2–3 programmes contribute most to the joint probability (the "load-bearing" choices in the portfolio).

top 7% top % of pool

Programs

12

Lyon 3 Business Law

Total capacity

209

seats

Avg access rate

8.9%

across tracks

Total applicants

7,897

N (confirmed)

Tier Distribution at µ = top 7%
HIGH REACH (<15%) 0
REACH (15-40%) 0
MATCH (40-80%) 0
SAFETY (>80%) 0
Track
N
C
R
A%
Intensity (N/C)
Inflation (R/C)
Yield%
P(admit)
Classification
N = confirmed candidacies · C = overall seats · R = last called rank · A% = R/N · N/C = demand intensity · R/C = offer inflation · Yield% = C/R · P% = Φ((A%−µ)/σ)

This use case illustrates how an AI assistant can leverage indicators from the MonMaster database to perform an advanced, probabilistic admission portfolio analysis.

By guiding the AI with a structured prompt, it crosses raw metrics (confirmed candidacies, seats capacity, and last called rank) to compute demand intensity, offer inflation, and admission probabilities.


Statistical Findings for Lyon 3

Based on the data extracted from the MCP server for the Business Law mention at Université Jean Moulin Lyon 3, the AI highlighted several key structural insights:

1. High Selection Across All Tracks

For an average candidate, Lyon 3’s Business Law catalogue is predominantly a HIGH REACH cluster (admittance probability $<15%$). The most accessible track in terms of raw acceptance rate is Droit Privé International et Comparé (18.1%), which only transitions into a REACH label for candidates in the top 14% of the pool.

2. Offer Inflation (High R/C Ratio)

Three programs — Coopération Économique, Droit International & Comparé, and Risques Émergents — show $R/C$ ratios above 5.4×. This indicates that their waitlist moves very deep, issuing 5 to 6 times more admission offers than actual seats. This offsets low conversion yields (15–18%).

3. Micro-Cohort Variance

Tracks like Droit International & Comparé and Coopération Économique only offer 10 seats. At this small scale, minor candidate shifts (2 or 3 student choices) can swing the acceptance rate by 3 to 5 percentage points, introducing higher estimation variance.


Step-by-Step Dashboard Guide

Adjust the dashboard below to evaluate your application profile:

  1. Pool Percentile µ Slider: Move the slider to represent your estimated percentile in the application pool (e.g. top 7% means you estimate your folder is in the top 7% of applicants).
  2. Joint Probability (Portfolio Tab): Computes the probability of receiving at least one offer from your chosen MATCH or SAFETY programs.
  3. Interactive Scatter Chart (Chart Tab): Displays raw demand $N$ against acceptance selectivity $A%$, with coordinate tooltips showing all derived metrics.