Ch14: Add --explain mode to tutoring A/B analyzer

Summary

No response

Details

Summary

Add an --explain mode to the Chapter 14 tutoring A/B case study analyzer
(scripts/ch14_tutoring_ab.py).

When --explain is set, the script should print human-readable explanations
alongside the numerical results (effect size, confidence interval, p-value).

Goals

• Add a --explain flag to the CLI (using the shared base_parser).
• When --explain is true:
  • Print brief, plain-language commentary on:
    • the estimated mean difference,
    • the 95% confidence interval,
    • the p-value and what it implies.
• Keep the default non-explain mode output unchanged (so existing workflows don’t break).
• Add at least one small test or example to show the new flag in action.

Hints

• Look at how scripts/ch14_tutoring_ab.py currently uses the CLI helper.
• Mirror the style of printouts used in Chapter 13/14 (short, clear, instructor-friendly).
• It’s fine to start with very minimal natural-language text; we can refine wording in review.

Difficulty

Beginner-friendly: good first issue for someone comfortable with basic Python
and the command line.

Files to Touch

No response

Contributor Checklist

• I have read CONTRIBUTING.md.
• I can run make lint locally.
• I can run make test locally.
• I have checked for existing issues/PRs that might overlap.

Start by reading scripts/ch14_tutoring_ab.py and how it uses the shared base_parser, then compare the printout style in the Chapter 13/14 examples. Add the --explain behavior while preserving the default output, and include a small test or example demonstrating the flag; run make test and make lint before checking the numerical explanations.