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George throws a ball at a target 15 times - Edexcel - A-Level Maths Statistics - Question 1 - 2022 - Paper 1

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George throws a ball at a target 15 times. Each time George throws the ball, the probability of the ball hitting the target is 0.48. The random variable X represen... show full transcript

Worked Solution & Example Answer:George throws a ball at a target 15 times - Edexcel - A-Level Maths Statistics - Question 1 - 2022 - Paper 1

Step 1

Find P(X = 3)

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Answer

To find the probability P(X=3)P(X = 3), we use the binomial probability formula:

P(X=k)=(nk)pk(1p)nkP(X = k) = \binom{n}{k} p^k (1-p)^{n-k}

where n=15n = 15 (number of trials), k=3k = 3 (number of successes), and p=0.48p = 0.48 (probability of success).

Calculating this gives:

P(X=3)=(153)(0.48)3(0.52)12P(X = 3) = \binom{15}{3} (0.48)^3 (0.52)^{12}

Calculating (153)\binom{15}{3}:

(153)=15!3!(153)!=455\binom{15}{3} = \frac{15!}{3!(15-3)!} = 455

Now substituting the values:

P(X=3)=455×(0.48)3×(0.52)12P(X = 3) = 455 \times (0.48)^3 \times (0.52)^{12}

Evaluating this gives approximately 0.01970.0197.

Step 2

Find P(X > 5)

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To find P(X>5)P(X > 5), we can use the complement rule:

P(X>5)=1P(X5)P(X > 5) = 1 - P(X \leq 5)

We first need to calculate P(X5)P(X \leq 5), which can be done using the binomial distribution:

P(X5)=P(X=0)+P(X=1)+P(X=2)+P(X=3)+P(X=4)+P(X=5)P(X \leq 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5)

Calculating each of these using the binomial probability formula for k=0,1,2,3,4,5k = 0, 1, 2, 3, 4, 5, we sum the probabilities to find:

P(X5)0.0799P(X \leq 5) \approx 0.0799

Now, substitute into the complement formula:

P(X>5)=10.07990.9201P(X > 5) = 1 - 0.0799 \approx 0.9201

Step 3

Use a normal approximation to calculate the probability that he will hit the target more than 110 times

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For part (b), we consider a normal approximation to the binomial distribution as George now throws the ball 250 times.

The random variable YY, representing the number of hits, can be approximated by the normal distribution:

YN(np,np(1p))Y \sim N(np, np(1-p))

where n=250n = 250 and p=0.48p = 0.48.

First, we calculate the mean and standard deviation:

  • Mean: μ=np=250×0.48=120\mu = np = 250 \times 0.48 = 120
  • Variance: σ2=np(1p)=250×0.48×0.5230.0\sigma^2 = np(1-p) = 250 \times 0.48 \times 0.52 \approx 30.0
  • Standard Deviation: σ30.05.48\sigma \approx \sqrt{30.0} \approx 5.48

Next, we standardize the target of 110 hits:

Z=Xμσ=1101205.481.83Z = \frac{X - \mu}{\sigma} = \frac{110 - 120}{5.48} \approx -1.83

Using the standard normal distribution table, we find:

P(Z>1.83)0.968P(Z > -1.83) \approx 0.968

Thus, the probability that George will hit the target more than 110 times is approximately 0.9680.968.

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