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sertanlavr [38]
3 years ago
12

Solve p(x+q)=r for x.

Mathematics
2 answers:
alisha [4.7K]3 years ago
5 0
Divide each side by p
P(x+q)/p=r/p
X+q=r/p
Subtract q from each side
X=r/p-q
algol133 years ago
4 0

Answer:

the answer is in the ss below

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Integrated circuits consist of electric channels that are etched onto silicon wafers. A certain proportion of circuits are defec
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Answer:

z=\frac{0.033 -0.05}{\sqrt{\frac{0.05(1-0.05)}{1000}}}=-2.467  

p_v =P(Z>-2.467)=0.0068  

So the p value obtained was a very low value and using the significance level assumed for example \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of circuits that show evidence of undercutting is significantly less than 0.05.  

Step-by-step explanation:

1) Data given and notation  

n=1000 represent the random sample taken

X=33 represent the number of circuits that show evidence of undercutting

\hat p=\frac{33}{1000}=0.033 estimated proportion of circuits that show evidence of undercutting

p_o=0.05 is the value that we want to test

\alpha represent the significance level

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that they reduce the rate of undercutting to less than 5%.:  

Null hypothesis:p\geq 0.05  

Alternative hypothesis:p < 0.05  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

3) Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.033 -0.05}{\sqrt{\frac{0.05(1-0.05)}{1000}}}=-2.467  

4) Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The next step would be calculate the p value for this test.  

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

p_v =P(Z>-2.467)=0.0068  

So the p value obtained was a very low value and using the significance level assumed for example \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of circuits that show evidence of undercutting is significantly less than 0.05.  

4 0
3 years ago
Keith Rollag (2007) noticed that coworkers evaluate and treat "new" employees differently from other staff members. He was inter
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Answer:

a) Real range of employees hired by each organization surveyed = 56

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Step-by-step explanation:

a) Note: To get the real range of employees hired by each organization, you would do a head count from 34 to 89 employees. This means that this can be done mathematically by finding the difference between 34 and 89 and add the 1 to ensure that "34" is included.

Real range of employees hired by each organization surveyed = (89 - 34) + 1

Real range of employees hired by each organization surveyed = 56

b) It is clearly stated in the question that  the "new" employee status was mostly reserved for the 30% of employees in the organization with the lowest tenure.

Therefore, the cumulative percent of "new" employees with the lowest tenure = 30%

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