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A machine cuts strips of metal to length $L$ cm, where $L$ is normally distributed with standard deviation 0.5 cm - Edexcel - A-Level Maths Statistics - Question 3 - 2017 - Paper 2

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A machine cuts strips of metal to length $L$ cm, where $L$ is normally distributed with standard deviation 0.5 cm. Strips with length either less than 49 cm or grea... show full transcript

Worked Solution & Example Answer:A machine cuts strips of metal to length $L$ cm, where $L$ is normally distributed with standard deviation 0.5 cm - Edexcel - A-Level Maths Statistics - Question 3 - 2017 - Paper 2

Step 1

find the probability that a randomly chosen strip of metal can be used.

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Answer

To find the probability that a randomly chosen strip can be used, we need to determine the range of usable lengths.

The probability of lengths less than 49 cm or greater than 50.75 cm:

  1. Calculate the z-score for 50.98 cm: z=50.98500.5=1.96z = \frac{50.98 - 50}{0.5} = 1.96

  2. Use the z-score to find the probability:

    • From z-tables, P(L>50.98)=0.025P(L > 50.98) = 0.025.
  3. The probability that a strip can be used is: P(49<L<50.75)=1P(L<49)P(L>50.75)P(49 < L < 50.75) = 1 - P(L < 49) - P(L > 50.75)

  4. Thus, the probability can be calculated as: P(49<L<50.75)=P(L<50.75)P(L<49)=0.9104P(49 < L < 50.75) = P(L < 50.75) - P(L < 49) = 0.9104 Therefore, the probability that a strip can be used is approximately 0.910.

Step 2

Find the probability fewer than 4 of these strips cannot be used.

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Answer

  1. The total number of strips selected is 10, and we previously calculated that the probability of a strip not being usable is 1P(49<L<50.75)=0.0901 - P(49 < L < 50.75) = 0.090.

  2. To find the probability that fewer than 4 strips cannot be used, use the binomial distribution: P(X<4)=P(X=0)+P(X=1)+P(X=2)+P(X=3)P(X < 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) where XX follows the distribution XB(n=10,p=0.090)X \sim B(n=10, p=0.090).

  3. Calculate each probability: P(X=k)=(nk)pk(1p)nkP(X = k) = \binom{n}{k} p^k (1-p)^{n-k}. Thus,

    • For k=0k=0: P(X=0)=(100)(0.090)0(0.910)10=0.91010approx0.348P(X=0) = \binom{10}{0}(0.090)^0(0.910)^{10} \\ = 0.910^{10} \\approx 0.348
    • For k=1k=1: P(X=1)=(101)(0.090)(0.910)9approx0.383P(X=1) = \binom{10}{1}(0.090)(0.910)^{9} \\approx 0.383
    • For k=2k=2: P(X=2)=(102)(0.090)2(0.910)8approx0.193P(X=2) = \binom{10}{2}(0.090)^2(0.910)^{8} \\approx 0.193
    • For k=3k=3: P(X=3)=(103)(0.090)3(0.910)7approx0.056P(X=3) = \binom{10}{3}(0.090)^3(0.910)^{7} \\approx 0.056
  4. Therefore, P(X<4)=P(X=0)+P(X=1)+P(X=2)+P(X=3)approx0.348+0.383+0.193+0.056=0.980P(X < 4) = P(X=0) + P(X=1) + P(X=2) + P(X=3) \\approx 0.348 + 0.383 + 0.193 + 0.056 = 0.980

Step 3

Stating your hypotheses clearly and using a 1% level of significance, test whether or not the mean length of all the strips, cut by the second machine, is greater than 50.1 cm.

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Answer

  1. Hypothesis Statement:

    • Null Hypothesis: H0:μ=50.1H_0: \mu = 50.1 cm
    • Alternative Hypothesis: H1:μ>50.1H_1: \mu > 50.1 cm
  2. Sample Mean and Standard Deviation:

    • Sample mean: Xˉ=50.4\bar{X} = 50.4 cm
    • Standard deviation: σ=0.6\sigma = 0.6 cm, sample size n=15n = 15.
  3. Calculate the z-score: z=Xˉμ0σ/n=50.450.10.6/15approx1.936z = \frac{\bar{X} - \mu_0}{\sigma / \sqrt{n}} = \frac{50.4 - 50.1}{0.6 / \sqrt{15}} \\approx 1.936

  4. Determine the p-value and compare with significance level:

    • For z=1.936z = 1.936, the p-value is approximately 0.02640.0264.
  5. Conclusion:

    • Since p=0.0264>0.01p = 0.0264 > 0.01, we fail to reject the null hypothesis. Hence, there is insufficient evidence to conclude that the mean length of strips is greater than 50.1 cm.

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