Question #230932

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. Assume that the mass of bread is approximately normally distributed 3.2 Polokwane Butchery supplies Vienna sausages in the entire of KZN province. An Inspector from the CCSA has been sceptical of the mass of the Vienna sausage packs after receiving numerous complaints. He wants to investigate the marked mass shown on Vienna sausages. A pilot study showed a mean of 11.8kg per pack and a variance of 0.49kg



1
Expert's answer
2021-09-01T16:08:25-0400

Given the information:

For a standard loaf of white bread,

Hypothesized mean μo=700\mu_o=700

Population standard deviation σ=21\sigma=21

Sample size n=64n=64

Sample mean x=695\overline{x}=695


We have given, mass of bread is approximately normally distributed.

Here we assume the level of significance α=0.05\alpha=0.05

Here to check if breads are overweight or not. We use z test statistic

Hypothesis to test

Ho:μ=700H_o:\mu=700

H1:μ>700H_1:\mu>700

Region rejection:

Zc=Zα=CriticalZ_c=Z_\alpha=Critical ValueValue

Where α=0.05\alpha=0.05

ZcZ_c is the critical value from Z - table at α=0.05\alpha=0.05

Therefore, Zc=Zα=1.645Z_c=Z_\alpha=1.645

Critical rejection region

R={Z:Z>1.645}R=\left\{Z:Z>1.645\right\}

Test statistic:

z=xμσn=6957002164=1.905z=\frac{\overline{x}-\mu }{\frac{\sigma }{\sqrt{n}}}=\frac{695-700}{\frac{21}{\sqrt{64}}}=-1.905

Decision rule:

z=1.905<Zc=1.645z=-1.905<Z_c=1.645

Hence we accept HoH_o at α=0.05\alpha=0.05

and we can conclude that there is no overweight production of bread.


Now, from ztablez-table we find out pvaluep-value for z=1.905z=-1.905

pvalue=p(z>1.905)p-value=p(z>-1.905)

=0.9716=0.9716

If pvalue>levelp-value>level ofof significance(α)significance(\alpha)

pvalue=0.9716>α=0.05p-value=0.9716>\alpha=0.05

Hence, we accept HoH_o at α=0.05\alpha=0.05

Conclusion

We can conclude that there is no overweight production of bread.


3.2

Given:

Sample mean (x)=11.8(\overline{x})=11.8

Sample variation (s)2=0.49(s)^2=0.49

Sample standard deviation (s)=s2(s)=\sqrt{s^2}

=0.49=\sqrt{0.49}

s=0.7s=0.7

Margin error =0.2=0.2

Confidence level(CI) =99=99%

We have to find out how many packs should the inspector sample out

In short we have to find out sample size.

We know that,

ConfidenceInterval=x±marginoferrorConfidence\:Interval=\overline{x}\:\pm margin\:of\:error

=x±Zα(sn)=\overline{x}\:\pm Z\alpha \left(\frac{s}{\sqrt{n}}\right)

Here we have given margin of error

Margin of error =Zα×(sn)=Z\alpha \times(\frac{s}{\sqrt{n}})

0.2=Zα×(0.7n)0.2=Z\alpha \times \left(\frac{0.7}{\sqrt{n}}\right)

Where, ZαZ\alpha is a critical value derived from zstatisticalz-statistical tabletable

For confidence level =99=99%

(1α)=0.99(1-\alpha)=0.99

α=0.01\alpha=0.01

Zα=0.01=2.576Z\alpha=0.01=2.576

0.2=2.576×(0.7n)0.2=2.576\times \left(\frac{0.7}{\sqrt{n}}\right)

n=(2.576×0.70.2)2n=\left(\frac{2.576\times 0.7}{0.2}\right)^2

n=80.7281n=80.72\approx 81

Therefore, we can say that 81 samples are required to find out 99% confidence that sample mean will differ by 0.2g.


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