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exis [7]
2 years ago
11

A production line operates with a mean filling weight of 16 ounces per container. Overfilling or underfilling presents a serious

problem and when detected requires the operator to shut down the production line to readjust the filling mechanism. From past data, a population standard deviation S=.8 ounces is assumed. A quality control in inspector selects a sample of 30 items every hour and at that time makes the decision of whether to shut down the line for readjustment. The level of significance is a = .05.- State the hypothesis test for this quality control application.- If a sample mean of xbar=16.32 ounces were found, what is the p-value ? What action would you recommend ?- If a sample mean of xbar=15.82 ounces were found, what is the p-value ? What action would you recommend ?- Use the critical value approach. What is the rejection rule for the preceding hypothesis testing procedure ? Repeat the last two parts : Do you reach the same conclusion ?
Mathematics
1 answer:
Dominik [7]2 years ago
5 0

Answer:

Part1) z=\frac{16.32-16}{\frac{0.8}{\sqrt{30}}}=2.191    

p_v =2*P(Z>2.191)=0.0284

Readjustment is needed

Part 2)  z=\frac{15.82-16}{\frac{0.8}{\sqrt{30}}}=-1.232    

z=\frac{15.82-16}{\frac{0.8}{\sqrt{30}}}=-1.232    

p_v =2*P(Z

No readjustment is needed

Step-by-step explanation:

Data given and notation

Part 1    

\bar X=16.32 represent the sample mean    

\sigma=0.8 represent the population standard deviation    

n=30 sample size    

\mu_o =16 represent the value that we want to test    

\alpha=0.05 represent the significance level for the hypothesis test.    

z would represent the statistic (variable of interest)    

p_v represent the p value for the test (variable of interest)    

State the null and alternative hypotheses.    

We need to apply a two tailed test.    

What are H0 and Ha for this study?    

Null hypothesis:  \mu =16    

Alternative hypothesis :\mu \neq 16    

Compute the test statistic  

The statistic for this case is given by:    

z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}} (1)    

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".    

Calculate the statistic    

We can replace in formula (1) the info given like this:    

z=\frac{16.32-16}{\frac{0.8}{\sqrt{30}}}=2.191    

Give the appropriate conclusion for the test  

Since is a two tailed test the p value would be:    

p_v =2*P(Z>2.191)=0.0284

Using the value of \alpha =0.05 we see that pv and we have enough evidence to reject the null hypothesis.

Readjustment is needed

The rejection zone is given by:

(-\infty ;-1.96) , (1.96;\infty)    

Part 2

\bar X=15.82 represent the sample mean    

We can replace in formula (1) the info given like this:    

z=\frac{15.82-16}{\frac{0.8}{\sqrt{30}}}=-1.232    

Give the appropriate conclusion for the test  

Since is a two tailed test the p value would be:    

p_v =2*P(Z

Using the value of \alpha =0.05 we see that pv>\alpha and we have enough evidence to FAIL to reject the null hypothesis.

No readjustment is needed

The rejection zone is given by:

(-\infty ;-1.96) , (1.96;\infty)  

What action would you recommend ?

Review the procedure.

Do you reach the same conclusion ?

No we got different conclusions

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bixtya [17]

Answer: 585 maybe??

Step-by-step explanation:

450/100 = 4.5

4,5 = 1 percent of the total amount.

4.5 x 25 = 112.5

112 = 25 percent of 450

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Hope u understand and that this helps:)

4 0
1 year ago
The article "Expectation Analysis of the Probability of Failure for Water Supply Pipes"† proposed using the Poisson distribution
oksian1 [2.3K]

Answer:

a. P(X ≤ 5) = 0.999

b. P(X > λ+λ) = P(X > 2) = 0.080

Step-by-step explanation:

We model this randome variable with a Poisson distribution, with parameter λ=1.

We have to calculate, using this distribution, P(X ≤ 5).

The probability of k pipeline failures can be calculated with the following equation:

P(k)=\lambda^{k} \cdot e^{-\lambda}/k!=1^{k} \cdot e^{-1}/k!=e^{-1}/k!

Then, we can calculate P(X ≤ 5) as:

P(X\leq5)=P(0)+P(1)+P(2)+P(4)+P(5)\\\\\\P(0)=1^{0} \cdot e^{-1}/0!=1*0.3679/1=0.368\\\\P(1)=1^{1} \cdot e^{-1}/1!=1*0.3679/1=0.368\\\\P(2)=1^{2} \cdot e^{-1}/2!=1*0.3679/2=0.184\\\\P(3)=1^{3} \cdot e^{-1}/3!=1*0.3679/6=0.061\\\\P(4)=1^{4} \cdot e^{-1}/4!=1*0.3679/24=0.015\\\\P(5)=1^{5} \cdot e^{-1}/5!=1*0.3679/120=0.003\\\\\\P(X\leq5)=0.368+0.368+0.184+0.061+0.015+0.003=0.999

The standard deviation of the Poisson deistribution is equal to its parameter λ=1, so the probability that X exceeds its mean value by more than one standard deviation (X>1+1=2) can be calculated as:

P(X>2)=1-(P(0)+P(1)+P(2))\\\\\\P(0)=1^{0} \cdot e^{-1}/0!=1*0.3679/1=0.368\\\\P(1)=1^{1} \cdot e^{-1}/1!=1*0.3679/1=0.368\\\\P(2)=1^{2} \cdot e^{-1}/2!=1*0.3679/2=0.184\\\\\\P(X>2)=1-(0.368+0.368+0.184)=1-0.920=0.080

4 0
1 year ago
A waiter at a restaurant has diarrhea what should happen?
Vilka [71]
The waiter should go home. It is because it is improper with regards to food safety and pathogenic bacteria such as E.coli can contaminate the food. Though the productivity of the restaurant will decrease, food safety must come first to reduce customer complaints.
8 0
1 year ago
Explain two different squares that can be made using the number 9
DedPeter [7]
One square can be a 3 by 3 square, meaning each side is 3 units.The area for this would be 9.

Another one is the square can be a 9 by 9 square, meaning each side is 9 units. The area for this would be 81.

3 0
1 year ago
If ∠BAC = 17° and ∠CED = 17° are the two triangles, ΔBAC and ΔCED similar? If so, by what criterion?
Alborosie

No, not possible to tell that the the two triangles, ΔBAC and ΔCED

are similar ⇒ answer D

Step-by-step explanation:

Let us revise the cases of similarity

1. AAA similarity : two triangles are similar if all three angles in the first

  triangle equal the corresponding angle in the second triangle  

2. AA similarity : If two angles of one triangle are equal to the

   corresponding angles of the other triangle, then the two triangles  

   are similar.

3. SSS similarity : If the corresponding sides of the two triangles are

   proportional, then the two triangles are similar.

4. SAS similarity : In two triangles, if two sets of corresponding sides  

   are proportional and the included angles are equal then the two  

   triangles are similar.

In the two triangles BAC and CED

∵ m∠BAC = 17°

∵ m∠CED = 17°

∴ m∠BAC = m∠CED

But we need another pair of angles to prove that the two triangles are

similar by AA similarity criterion

<em>OR </em>

The lengths of sides BA , CA and CE , DE to show that

\frac{BA}{CE}=\frac{CA}{DE} = constant ratio and prove that the

two triangles are similar by SAS similarity criterion

So it is not possible to prove that the two triangles are similar

No, not possible to tell that the the two triangles, ΔBAC and ΔCED

are similar

Learn more:

You can learn more about triangles in brainly.com/question/4354581

#LearnwithBrainly

5 0
2 years ago
Read 2 more answers
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