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Lisa [10]
3 years ago
9

QUESTION THREE (30 MARKS) 3.1 The mass of a standard loaf of white bread is, by law meant to be 700g with a population standard

deviation of 21g. The Lauren Bakery, which supplies outlets throughout the Eastern Cape, regularly checks the masses of its standard loaf of bread white bread. If their bread is underweight, on average, they are liable for a fine by the Provincial Department of Health, whose inspectors undertake random checks. If the bread is overweight, on average, the bakery is wasting its ingredients. On a given day, a random sample of 64 loaves is selected and weighed. The sample mean mass was found to be 695g. (15) Assume that the mass of bread is approximately normally distributed.​
Mathematics
1 answer:
kiruha [24]3 years ago
7 0

Using the normal distribution and the central limit theorem, it is found that  there is a 0.0284 = 2.84% probability of finding a sample mean mass of 695g or below.

----------------------------------

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

----------------------------------

  • Mean of 700g means that \mu = 700
  • Standard deviation of 21g means that \sigma = 21
  • Sample of 64, thus n = 64
  • <u>For the sampling distribution of the sample mean</u>, the standard deviation is of s = \frac{21}{\sqrt{64}} = \frac{21}{8} = 2.625

The probability of finding a sample mean mass of 695g or below is the p-value of Z when X = 695, thus:

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{695 - 700}{2.625}

Z = -1.905

Z = -1.905 has a p-value of 0.0284.

0.0284 = 2.84% probability of finding a sample mean mass of 695g or below.

A similar problem is given at brainly.com/question/22934264

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