Exercise 1: Classifying Discrete vs. Continuous Quantities — Possible Solution
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(a) THE NUMBER OF USERS CURRENTLY LOGGED IN — DISCRETE
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At any given moment, there is a specific whole number of logged-in
users - 0, 1, 2, 3, and so on. There's no meaningful sense in which
"7.3 users" could be logged in. Per this chapter's own definition,
discrete values are "distinct, separate, countable - you can list them
one by one," which is exactly what a user count is.

(b) THE EXACT CPU TEMPERATURE AT A GIVEN INSTANT — CONTINUOUS
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Temperature is a physical quantity that varies smoothly - between any
two temperature readings, arbitrarily many intermediate values exist
(45.10°C, 45.101°C, 45.1001°C, and so on without any natural stopping
point). This matches the chapter's own definition of continuous values:
"between any two values, infinitely many more exist." That a sensor
eventually reports a rounded reading is a limitation of measurement,
not a property of temperature itself.

(c) THE NUMBER OF ROWS RETURNED BY A SQL QUERY — DISCRETE
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A result set contains a specific whole number of rows - 0, 1, 100, or
however many actually matched. Rows can't exist in fractional
quantities; you can list them one by one, exactly matching the
chapter's own definition of discrete.

(d) THE AMOUNT OF TIME A FUNCTION TOOK TO EXECUTE — CONTINUOUS
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Execution time is fundamentally a measurement of duration, which - like
temperature - can, in principle, take any value along a continuous
range (12.4ms, 12.41ms, 12.403ms, and so on). That a computer's clock
has finite resolution and eventually rounds the measurement doesn't
change what kind of quantity time actually is; it's continuous by
nature, discrete only in how it happens to get measured.

WHY THIS WORKS AS AN ANSWER
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Each classification is justified directly against the chapter's own
definitions - discrete quantities are countable and listable one by
one; continuous quantities allow infinitely many intermediate values
between any two points. Two examples (user count, row count) are
naturally whole-number quantities with no meaningful fractional values;
two examples (temperature, execution time) are physical measurements
that vary smoothly, even though real-world sensors and clocks report
them with finite precision.