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IB Mathematics: Applications and Interpretation SL · 13.2: Probability Distributions · 13.2.1
Discrete random variables and distribution tables Problem set B Worked solutions
Skills
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A drawing pin lands point up with probability 0.35. It is dropped twice. X is the number of times it lands point up.
(a) Write the probability distribution of X as a table.
- \(P(X=0)=0.65\times0.65=0.4225\)
- \(P(X=1)=2\times0.35\times0.65=0.455\)
- \(P(X=2)=0.35\times0.35=0.1225\)
- The probabilities add to 1.
(b) Find P(X ≥ 1).
- \(P(X\ge1)=1-P(X=0)=1-0.4225=0.5775\)
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A wheel is split into 12 equal sectors numbered 1 to 12. It is spun once and X is the number it stops on.
(a) Write down P(X = x) for each score.
- The 12 scores are equally likely.
- \(P(X=x)=\frac1{12}\)
(b) Find P(X ≥ 10).
- 3 scores are 10 or more.
- \(P(X\ge10)=\frac{3}{12}=\frac{1}{4}\)
(c) Find P(4 ≤ X ≤ 7).
- 4 scores from 4 to 7.
- \(P(4\le X\le7)=\frac{4}{12}=\frac{1}{3}\)
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The table shows the probability distribution of X, the number of siblings of a student in a class.
(a) Find the value of k.
- \(0.22 + 0.38 + 0.09 + 0.05+k=1\)
- \(k=1-0.74=0.26\)
(b) Find P(X ≤ 1).
- \(P(X\le1)=P(X=0)+P(X=1)=0.22+0.38=0.6\)
(c) Find P(X ≥ 3).
- \(P(X\ge3)=P(X=3)+P(X=4)=0.09+0.05=0.14\)
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The probability that a train is late on any one day is 0.2. The days are independent. X is the number of late trains on a three-day trip.
(a) Write the probability distribution of X as a table.
- \(P(X=0)=0.8^3=0.512\)
- \(P(X=1)=3\times0.2\times0.8^2=0.384\)
- \(P(X=2)=3\times0.2^2\times0.8=0.096\)
- \(P(X=3)=0.2^3=0.008\)
- The four probabilities add to 1.
(b) Find P(X ≥ 2).
- \(P(X\ge2)=P(X=2)+P(X=3)=0.096+0.008=0.104\)
In context
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A teacher chooses 2 students at random from a group of 3 boys and 6 girls. X is the number of boys chosen.
(a) Write the probability distribution of X as a table.
- \(P(X=0)=\frac{6}{9}\times\frac{5}{8}=\frac{5}{12}\)
- \(P(X=1)=2\times\frac{3}{9}\times\frac{6}{8}=\frac{1}{2}\)
- \(P(X=2)=\frac{3}{9}\times\frac{2}{8}=\frac{1}{12}\)
- Check: the three probabilities add to 1.
(b) Find P(X ≥ 1).
- \(P(X\ge1)=1-P(X=0)=1-\frac{5}{12}=\frac{7}{12}\)
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Three cards are drawn one at a time, with replacement, from ten cards numbered 1 to 10. X is the number of times the card showing 10 is drawn.
(a) Write the probability distribution of X as a table.
- \(P(X=0)=\left(0.9\right)^3=0.729\)
- \(P(X=1)=3\times0.1\times\left(0.9\right)^2=0.243\)
- \(P(X=2)=3\times\left(0.1\right)^2\times0.9=0.027\)
- \(P(X=3)=\left(0.1\right)^3=0.001\)
- The four probabilities add to 1.
(b) Find P(X ≥ 1).
- \(P(X\ge1)=1-P(X=0)=0.271\)
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The table shows the probability distribution of R, the number of puncture repairs a cycle shop does in a day.
(a) Find the value of k.
- \(0.21 + 0.33 + 0.24 + 0.13+k=1\)
- \(k=0.09\)
(b) Find P(R ≥ 2).
- \(P(R\ge2)=0.24+0.13+0.09=0.46\)
(c) Find P(R ≥ 3 | R ≥ 2).
- \(P(R\ge3\mid R\ge2)=\frac{P(R\ge3)}{P(R\ge2)}=\frac{0.22}{0.46}=0.478\)
Stretch
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A discrete random variable X has the distribution shown, where k is a constant.
(a) Show that k² + 3k − 0.31 = 0.
- \(k^2+k+2k+0.69=1\)
- \(k^2+3k-0.31=0\)
(b) Use your calculator to solve this equation and state the value of k.
- Polynomial solver, coefficients 1, 3, −0.31: k = 0.1 or k = −3.1
- A probability cannot be negative, so reject the negative root.
- \(k=0.1\)
(c) Find P(X ≥ 3).
- \(P(X\ge3)=P(X=3)+P(X=4)=2k+0.69=0.89\)
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A team of 3 is chosen at random from 5 girls and 3 boys. X is the number of boys in the team.
(a) Write the probability distribution of X as a table.
- \(P(X=0)=\frac{5}{8}\times\frac{4}{7}\times\frac{3}{6}=\frac{5}{28}\)
- \(P(X=1)=3 \times \frac{3}{8}\times\frac{5}{7}\times\frac{4}{6}=\frac{15}{28}\)
- \(P(X=2)=3 \times \frac{3}{8}\times\frac{2}{7}\times\frac{5}{6}=\frac{15}{56}\)
- \(P(X=3)=\frac{3}{8}\times\frac{2}{7}\times\frac{1}{6}=\frac{1}{56}\)
- Check: the four probabilities add to 1.
(b) Find P(X ≥ 1).
- \(P(X\ge1)=1-P(X=0)=1-\frac{5}{28}=\frac{23}{28}\)
(c) Find P(X = 2 | X ≥ 1).
- \(P(X=2\mid X\ge1)=\frac{\frac{15}{56}}{\frac{23}{28}}=\frac{15}{46}=0.326\)
jmaths.xyz · AI SL · 13.2.1 Discrete random variables and distribution tables