Lesson 4B.2.1
4B.2.1 Probability density functions Quiz: Pearson Edexcel Further Maths, Unit 19
20 questions
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Lesson 4B.2.1, Probability density functions: 20 multiple choice questions for the Pearson Edexcel Further Maths (9FM0), Unit 19: Continuous random variables, written with Revision Ninja.
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The 20 questions
-
Which two conditions must the probability density function f(x) of a continuous random variable satisfy?
- f(x) equals P(X = x) for each x, and the sum of f(x) over all x equals 1
- f(x) is always increasing, and f(x) equals 1 at the mean of X
- f(x) is never negative, and the integral of f(x) over all x equals 1
- f(x) is never greater than 1, and the integral of f(x) over all x equals 0
-
For a continuous random variable X, what is P(X = c) for any single value c?
- 1 divided by the number of values that X can take
- F(c), the cumulative distribution function evaluated at c
- f(c), the value of the probability density function at c
- 0, because the probability is an area under the curve over a zero-width interval
-
Which expression gives P(a < X <= b) for a continuous random variable X with pdf f(x)?
- f(b) minus f(a)
- The integral of x f(x) with respect to x from a to b
- f(a) multiplied by (b minus a)
- The integral of f(x) with respect to x from a to b
-
A continuous random variable has pdf f(x) = 1/4 for 2 <= x <= 6 and 0 otherwise. What is P(X > 5)?
- 0.25
- 0.75
- 0.5
- 0.4
-
The pdf of a continuous random variable can take values greater than 1 at some points. Which statement explains why this is allowed?
- Only the total area under the pdf must equal 1, so individual heights can exceed 1
- The pdf must be symmetric about the mean, so heights above 1 are always allowed
- The pdf gives probabilities directly, so each height must lie between 0 and 1
- The pdf must always be at most 1 for every x, so this is impossible
-
Which of the following is a valid pdf on the interval [0, 1]?
- f(x) = 2 - x on [0, 1], since its height is positive throughout
- f(x) = 3x^2 on [0, 2], since it is never negative and its height is at most 12
- f(x) = 3x^2 on [0, 1], since its integral over [0, 1] is 1
- f(x) = x^2 on [0, 1], since it is never negative
-
For a pdf f, what does the integral from minus infinity to x0 of f(t) dt represent?
- The probability that X equals x0 exactly
- P(X <= x0), the cumulative distribution function at x0
- The value of the pdf at x0
- The mean of X for all values up to x0
-
For a continuous random variable with cdf F, which expression gives P(X > a)?
- the value F(a) itself
- 1 minus the density value f(a)
- 1 minus F(a)
- the density value f(a)
-
A continuous random variable has pdf f(x) = k x^2 for 0 <= x <= 2 and 0 otherwise. What is the value of k?
- 1/2
- 3/4
- 3/8
- 1/8
-
A continuous random variable has pdf f(x) = (3/8) x^2 for 0 <= x <= 2 and 0 otherwise. What is P(X < 1)?
- 1/8
- 3/8
- 1/3
- 1/2
-
A continuous random variable has pdf f(x) = 2x for 0 <= x <= 1 and 0 otherwise. What is P(X > 0.5)?
- 0.375
- 0.25
- 0.5
- 0.75
-
A continuous random variable has pdf f(x) = (3/4)(1 - x^2) for -1 <= x <= 1 and 0 otherwise. What is P(0 < X < 1)?
- 3/4
- 1/2
- 1/4
- 3/8
-
A continuous random variable has pdf f(x) = x/8 for 0 <= x <= 4 and 0 otherwise. What is P(X > 3)?
- 3/8
- 1/4
- 7/16
- 1/2
-
A continuous random variable has pdf f(x) = c e^(-x) for x >= 0 and 0 otherwise. What is the value of c?
- e
- 1
- 1/e
- 2
-
A continuous random variable has pdf f(x) = k(x + 1) for 0 <= x <= 2 and 0 otherwise. What is the value of k?
- 1/4
- 1/6
- 1/3
- 1/2
-
A continuous random variable has pdf f(x) = (3/32) x(4 - x) for 0 <= x <= 4 and 0 otherwise. What is P(X > 2)?
- 1/2
- 3/8
- 5/8
- 1/4
-
A continuous random variable has pdf f(x) = 4x^3 for 0 <= x <= 1 and 0 otherwise. What is P(X > 1/2)?
- 7/8
- 1/2
- 1/16
- 15/16
-
A continuous random variable has pdf f(x) = kx for 0 <= x <= 2 and f(x) = k(4 - x) for 2 < x <= 4, zero otherwise. What is k?
- 1/2
- 1/4
- 1/8
- 1/3
-
A continuous random variable has pdf f(x) = (3/8) x^2 for 0 <= x <= 2 and 0 otherwise. What is P(X > 1 given X > 1/2)?
- 8/9
- 7/8
- 1/2
- 63/64
-
A continuous random variable has pdf f(x) = kx for 0 <= x <= 1 and f(x) = k(2 - x) for 1 < x <= 2, zero otherwise. What is k?
- 1
- 2
- 1/4
- 1/2
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