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pentagon [3]
3 years ago
13

A cereal manufacturer is concerned that the boxes of cereal not be under filled or overfilled. Each box of cereal is supposed to

contain 13 ounces of cereal. A random sample of 36 boxes is tested. The sample average weight is 12.85 ounces and the sample standard deviation is 0.75 ounces. Use the critical-value approach to test whether the population average weight of a cereal box differs from 13 ounces. The critical-value should be:
Mathematics
1 answer:
Vaselesa [24]3 years ago
3 0

Answer:

We conclude that the population average weight of a cereal box is equal to 13 ounces.

Step-by-step explanation:

We are given that a cereal manufacturer is concerned that the boxes of cereal not be under filled or overfilled.

A random sample of 36 boxes is tested. The sample average weight is 12.85 ounces and the sample standard deviation is 0.75 ounces.

<u><em /></u>

<u><em>Let </em></u>\mu<u><em> = population average weight of a cereal box</em></u>

So, Null Hypothesis, H_0 : \mu = 13 ounces    {means that the population average weight of a cereal box is equal to 13 ounces}

Alternate Hypothesis, H_A : \mu \neq 13 ounces    {means that the population average weight of a cereal box differs from 13 ounces}

The test statistics that will be used here is <u>One-sample t test statistics</u> as we don't know about population standard deviation;

                                  T.S.  = \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample average weight = 12.85 ounces

            \sigma = sample standard deviation = 0.75 ounces

            n = sample of boxes = 36

So, <u><em>test statistics</em></u>  =  \frac{12.85-13}{\frac{0.75}{\sqrt{36} } }  ~ t_3_5

                               =  -1.20

The value of the test statistics is -1.20.

Since, in the question we are not given with the level of significance so we assume it to be 5%. Now at 5% significance level, <u>the t table gives critical values between -2.03 and 2.03 at 35 degree of freedom for two-tailed test</u>.

Since our test statistics lies within the range of critical values of t, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which <u>we fail to reject our null hypothesis</u>.

Therefore, we conclude that the population average weight of a cereal box is equal to 13 ounces.

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Soloha48 [4]

Answer:

We conclude that the vaccine appears to be​ effective.

Step-by-step explanation:

We are given that a doctor released the results of clinical trials for a vaccine to prevent a particular disease.

The subjects in group 1​ (the experimental​ group) were given the​ vaccine, while the subjects in group 2​ (the control​ group) were given a placebo. Of the 200 comma 000 children in the experimental​ group, 38 developed the disease. Of the 200 comma 000 children in the control​ group, 81 developed the disease.

Let<em> </em>p_1<em> = proportion of subjects in the experimental​ group who developed the disease.</em>

<em />p_2<em> = proportion of subjects in the control​ group who developed the disease.</em>

So, Null Hypothesis, H_0 : p_1\geq p_2       {means that the vaccine does not appears to be​ effective}

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The test statistics that would be used here <u>Two-sample z proportion</u> <u>statistics</u>;

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where, \hat p_1 = sample proportion of children in the experimental​ group who developed the disease = \frac{38}{200,000} =  0.00019

\hat p_2 = sample proportion of children in the control​ group who developed the disease = \frac{81}{200,000} =  0.00041

n_1 = sample of children in the experimental​ group = 200,000

n_2 = sample of children in the control​ group = 200,000

So, <u><em>test statistics</em></u>  =  \frac{(0.00019-0.00041)-(0)}{\sqrt{\frac{0.00019(1-0.00019)}{200,000}+\frac{0.00041(1-0.00041)}{200,000}  } }

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The value of z test statistics is -4.02.

Now, at 0.01 significance level the z table gives critical values of -2.33 for left-tailed test.

Since our test statistics is less than the critical value of z as -4.02 < -2.33, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u>we reject our null hypothesis</u>.

Therefore, we conclude that the vaccine appears to be​ effective.

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Answer:

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Answer:

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Answer:

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Step-by-step explanation:

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