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Probability Distributions for ML Practice Exam

Test yourself under real exam conditions: 50 timed questions, 60 on the clock, pass mark 70%%. Instant score with a full review of everything you got wrong. Free — no account needed.

📝 50 questions · ⏱ 60 minutes · 🎯 Pass mark 70% · 🆓 Free, no signup

Exam details

  • 50 questions drawn from 120 cards
  • Countdown timer — auto-submits when time runs out
  • Pass mark 70% (real certification threshold)
  • Full review of wrong answers at the end
  • No signup required — save your score with a free account

Sample Questions

5 shown

What is a probability distribution?

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A function (or rule) that assigns to every outcome in a sample space a non-negative probability, with the total probability over all outcomes summing (or integrating) to 1.

What is a discrete probability distribution?

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A distribution defined on a countable set of outcomes, specified by a probability mass function (PMF) p(x) with p(x) ≥ 0 and Σ p(x) = 1.

What is a probability mass function (PMF)?

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A function p(x) that gives the probability of a discrete random variable taking the value x; satisfies p(x) ≥ 0 for all x and Σ_x p(x) = 1.

What is a probability density function (PDF)?

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A function f(x) for a continuous random variable such that P(a ≤ X ≤ b) = ∫_a^b f(x) dx, with f(x) ≥ 0 and ∫_{-∞}^{∞} f(x) dx = 1.

What is the cumulative distribution function (CDF)?

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A function F(x) = P(X ≤ x). It is non-decreasing, right-continuous, lim_{x→-∞} F(x) = 0, and lim_{x→∞} F(x) = 1.

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