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Snezhnost [94]
2 years ago
12

a cylindrical tinfull of engine oil has a diameter of 12cmand the height of 14cm.the oil is poured into a rectangular tin 16cm l

ong and 11cm wide,what is the depth of the oil in the tin? ​
Mathematics
1 answer:
steposvetlana [31]2 years ago
3 0

Find the volume of the cylinder using the formula v = pixr^2 x height

V= 3.14 x 6^2 x 14 = 1,582.56 cubic cm

Area of of the rectangle = 16 x 11 = 176 square cm

The height will be the volume divided by the area

Height =1582.56/176 = 8.99 cm

The height is 8.99 cm ( round off as needed)

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A group of retired admirals, generals, and other senior military leaders, recently published a report, "Too Fat to Fight". The r
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Answer:

z=\frac{0.694 -0.75}{\sqrt{\frac{0.75(1-0.75)}{180}}}=-1.735  

p_v =P(z  

If we compare the p value obtained and the significance level given \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 americans between 17 to 24 that not qualify for the military is significantly less than 0.75 or 75% .  

Step-by-step explanation:

1) Data given and notation  

n=180 represent the random sample taken  

X=125 represent the number of americans between 17 to 24 that not qualify for the military

\hat p=\frac{125}{180}=0.694 estimated proportion of americans between 17 to 24 that not qualify for the military

p_o=0.75 is the value that we want to test  

\alpha=0.05 represent the significance level  

Confidence=95% or 0.95  

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 less than 75% of Americans between the ages of 17 to 24 do not qualify for the military :  

Null hypothesis: p\geq 0.75  

Alternative hypothesis:p < 0.75  

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{0.694 -0.75}{\sqrt{\frac{0.75(1-0.75)}{180}}}=-1.735  

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 significance level provided \alpha=0.05. 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  

If we compare the p value obtained and the significance level given \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 americans between 17 to 24 that not qualify for the military is significantly less than 0.75 or 75% .  

6 0
2 years ago
Does anyone know this and if it is extraneous or not?
Anna11 [10]
Addd 4 to both sides
\sqrt{x+9}=5
sqare both sides
x+9=25
minus 9 both sides
x=16

plug it in for x and see
\sqrt{16+9}-4=1
\sqrt{25}-4=1
5-4=1
1=1
true

not extraneous
an extraneous root would be x=-34
5 0
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The mean survivial time after diagnosis for a certain disease is 15 years with a standard deviation of 5 years. Based on a parti
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Answer:

The time the patient expected to survive after diagnosis is 29 years.

Step-by-step explanation:

It is provided that the mean survival time after diagnosis for a certain disease is 15 years with a standard deviation of 5 years.

That is,

\mu=15\\\sigma=5

An individual's predicted survival time is <em>a</em> = 2.8 standard deviations beyond the mean.

Compute the time the patient expected to survive after diagnosis as follows:

X=\mu+a\sigma

    =15+(2.8\times 5)\\\\=15+14\\\\=29

Thus, the time the patient expected to survive after diagnosis is 29 years.

5 0
3 years ago
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