Exercise 1: Descriptive/Model-Based or Inferential? — Possible Solution
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(A) COMPUTING THE AVERAGE OF 50 MEASURED RESPONSE TIMES — DESCRIPTIVE
(FUNDAMENTALS)
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This is a plain summary computed directly from data already in hand -
exactly Probability & Statistics Fundamentals' own Chapter 9 material.
No claim is being made about anything beyond these 50 specific
measurements.

(B) CLAIMING THE TRUE AVERAGE ACROSS ALL FUTURE REQUESTS LIKELY FALLS
BETWEEN 190MS AND 210MS — INFERENTIAL (THIS COURSE)
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This extends beyond the 50 measurements actually collected to make a
quantified claim about the true, unobserved population of ALL future
requests - exactly this chapter's own inferential direction, and
specifically the shape of a confidence interval (this course's own
Chapter 3).

(C) A KNOWN FAIR COIN, PROBABILITY OF 3 HEADS IN 5 FLIPS — PROBABILITY
(FUNDAMENTALS)
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The model (a fair coin) is already fully known and given; the question
reasons forward from that known model to a predicted outcome - exactly
Probability & Statistics Fundamentals' own probability direction, not
inference from limited data at all.

(D) DECIDING WHETHER A 2% LIFT IN A 2-WEEK EXPERIMENT IS REAL OR NOISE
— INFERENTIAL (THIS COURSE)
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This is precisely a hypothesis-testing / A-B-testing question - using
limited experimental data to draw a confident conclusion about whether
a genuine underlying effect exists, rather than simply describing the
2-week sample's own numbers. Exactly this course's own Chapters 4-6.

WHY THIS WORKS AS AN ANSWER
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Each classification is made by checking whether the reasoning stays
confined to describing the data already collected (descriptive, or
probability's forward reasoning from an already-known model) or
extends beyond that limited data to a confident claim about an
unobserved population (inferential), per this chapter's own
descriptive-vs-inferential distinction.