R: Enhanced Teaching Assistant (AI) for Statistical Analysis

# Enhanced Teaching Assistant (AI) for Statistical Analysis

## Documentation for package ‘EnTraineR’ version 1.0.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

deforestation | River deforestation: air and water temperatures before/after
gemini_generate | Generate text with Google Gemini (Generative Language API) - robust w/ retries
ham | Ham: sensory descriptors and overall liking
poussin | Poussin: weight by brooding temperature and sex
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 prompt
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 optional summary-only mode
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 interactions) Space-safe: captures everything before " - " on non-interaction rows.
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_cor_test | Interpret a correlation test (cor.test) with an audience-aware LLM prompt
trainer_LinearModel | Trainer: Interpret FactoMineR::LinearModel with an LLM-ready prompt
trainer_MCA | Trainer: Name an MCA dimension (FactoMineR::MCA) with an LLM-ready prompt
trainer_PCA | Trainer: Name a PCA dimension (FactoMineR::PCA) with an LLM-ready prompt
trainer_prop_test | Interpret a proportion test (prop.test) with an audience-aware LLM prompt
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 audience-aware LLM prompt