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A survey of 120 adults found that the volume, $X$ litres per person, of carbonated drinks they consumed in a week had the following results: $$\sum X = 165.6$$ $$\sum X^2 = 261.8$$ 16 (a) (i) Calculate the mean of $X$ - AQA - A-Level Maths: Pure - Question 16 - 2018 - Paper 3

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Question 16

A-survey-of-120-adults-found-that-the-volume,-$X$-litres-per-person,-of-carbonated-drinks-they-consumed-in-a-week-had-the-following-results:-$$\sum-X-=-165.6$$-$$\sum-X^2-=-261.8$$--16-(a)-(i)-Calculate-the-mean-of-$X$-AQA-A-Level Maths: Pure-Question 16-2018-Paper 3.png

A survey of 120 adults found that the volume, $X$ litres per person, of carbonated drinks they consumed in a week had the following results: $$\sum X = 165.6$$ $$\su... show full transcript

Worked Solution & Example Answer:A survey of 120 adults found that the volume, $X$ litres per person, of carbonated drinks they consumed in a week had the following results: $$\sum X = 165.6$$ $$\sum X^2 = 261.8$$ 16 (a) (i) Calculate the mean of $X$ - AQA - A-Level Maths: Pure - Question 16 - 2018 - Paper 3

Step 1

Calculate the mean of $X$.

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Answer

To calculate the mean of XX, we use the formula:

μ=∑Xn\mu = \frac{\sum X}{n}

where ∑X=165.6\sum X = 165.6 and n=120n = 120.

Thus, μ=165.6120=1.38\mu = \frac{165.6}{120} = 1.38

Step 2

Calculate the standard deviation of $X$.

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Answer

The standard deviation σ\sigma is calculated using the formula:

σ=∑X2n−(μ)2\sigma = \sqrt{\frac{\sum X^2}{n} - (\mu)^2}

Substituting the values:

  • ∑X2=261.8\sum X^2 = 261.8, so ∑X2n=261.8120≈2.18167\frac{\sum X^2}{n} = \frac{261.8}{120} \approx 2.18167
  • Already obtained mean μ=1.38\mu = 1.38, thus μ2=(1.38)2=1.9044\mu^2 = (1.38)^2 = 1.9044

Now, calculating:

σ=2.18167−1.9044≈0.27727≈0.526\sigma = \sqrt{2.18167 - 1.9044} \approx \sqrt{0.27727} \approx 0.526

Step 3

Assuming that $X$ can be modelled by a normal distribution find $P(0.5 < X < 1.5)$.

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Answer

To find P(0.5<X<1.5)P(0.5 < X < 1.5), we first standardize the variable:

Z=X−μσZ = \frac{X - \mu}{\sigma}

For X=0.5X = 0.5:

Z=0.5−1.380.526≈−1.677  ⟹  P(Z<−1.677)Z = \frac{0.5 - 1.38}{0.526} \approx -1.677 \implies P(Z < -1.677)

For X=1.5X = 1.5:

Z=1.5−1.380.526≈0.227  ⟹  P(Z<0.227)Z = \frac{1.5 - 1.38}{0.526} \approx 0.227 \implies P(Z < 0.227)

Using Z-tables or calculators:

P(0.5<X<1.5)=P(Z<0.227)−P(Z<−1.677)≈0.5910−0.0468=0.5442P(0.5 < X < 1.5) = P(Z < 0.227) - P(Z < -1.677) \approx 0.5910 - 0.0468 = 0.5442

Step 4

Find $P(X = 1)$.

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Answer

In a continuous distribution, the probability of P(X=1)P(X = 1) for any single point is 0. Therefore,

P(X=1)=0P(X = 1) = 0

Step 5

Determine whether a normal distribution is suitable to model this data.

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Answer

To determine if a normal distribution is appropriate, we should consider:

  • The calculated mean μ=1.38\mu = 1.38 and standard deviation σ≈0.526\sigma \approx 0.526.
  • Check for any significant skewness or outliers in the data distribution (this may require graphical analysis, like a histogram). If the values remain within reasonable limits and there are no outliers, it can be considered normal, otherwise it might not be suitable depending on the skewness observed.

Step 6

Find the value of $\mu$, correct to three significant figures.

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Answer

Given P(Y>0.75)=0.10P(Y > 0.75) = 0.10, we will use the Z-score formula:

P(Z≥z)=0.10  ⟹  z≈1.2816P(Z \geq z) = 0.10 \implies z \approx 1.2816

Thus, substituting into the Z-score formula:

0.75−μ0.21=−1.2816\frac{0.75 - \mu}{0.21} = -1.2816

Solving for μ\mu gives:

0.75−μ=−1.2816⋅0.210.75 - \mu = -1.2816 \cdot 0.21

Calculating:

−μ=−0.2681+0.75-\mu = -0.2681 + 0.75

Thus,

μ≈0.4819, correct to three significant figures gives μ=0.482\mu \approx 0.4819, \text{ correct to three significant figures gives } \mu = 0.482

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