EnTraineR1.0.0 package

Enhanced Teaching Assistant (AI) for Statistical Analysis

gemini_generate

Generate text with Google Gemini (Generative Language API) - robust w/...

trainer_AovSum

Trainer: Interpret ANOVA (AovSum) with an LLM-ready prompt

trainer_chisq_test

Interpret a chi-squared test (chisq.test) with an audience-aware LLM p...

trainer_cor_test

Interpret a correlation test (cor.test) with an audience-aware LLM pro...

trainer_core_actually_shown

Determine which requested items were actually shown after filtering

trainer_core_audience_profile

Build an audience profile (beginner / applied / advanced) with optiona...

trainer_core_build_prompt

Assemble a standard prompt with common sections

trainer_core_conf_label

Confidence level label helper

trainer_core_detect_main_factors

Detect main-effect factor names present in T-test lines (ignore intera...

trainer_core_extract_block_after

Extract lines following a header (up to first blank line)

trainer_core_filter_ttest_by_factors

Filter T-test lines by requested factors (main and/or interactions)

trainer_core_generate_or_return

Generate or return a prompt, depending on generate

trainer_core_llm_generate

LLM generation helper for TraineR

trainer_core_prompt_header

Build the standard header for prompts

trainer_core_summary_only_block

Utility: render a standard 3-bullet summary-only instruction

trainer_core_ttest_scope_msg

Scope message for T-test section based on requested & found factors

trainer_LinearModel

Trainer: Interpret FactoMineR::LinearModel with an LLM-ready prompt

trainer_MCA

Trainer: Name an MCA dimension (FactoMineR::MCA) with an LLM-ready pro...

trainer_PCA

Trainer: Name a PCA dimension (FactoMineR::PCA) with an LLM-ready prom...

trainer_prop_test

Interpret a proportion test (prop.test) with an audience-aware LLM pro...

trainer_t_test

Interpret a Student's t-test (stats::t.test) with an LLM-ready prompt

trainer_var_test

Interpret an F test comparing two variances (var.test) with an audienc...

An assistant built on large language models that helps interpret statistical model outputs in R by generating concise, audience-specific explanations.

  • Maintainer: Sébastien Lê
  • License: MIT + file LICENSE
  • Last published: 2026-01-17