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zavuch27 [327]
3 years ago
10

Simplify this complex fraction.

Mathematics
1 answer:
soldier1979 [14.2K]3 years ago
5 0

answer: 6 3/4

you divide 1/3 by 2 1/4

= 1/3 / 9/4

= 3/1 x 9/4

= 27/4

= 6 3/4

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BRAINIEST TO CORRECT ANSWER<br> (2x^2 +7x)+ (−x^2+10x+3)
Finger [1]

Answer: x2+17x+3

Step-by-step explanation:

2x2+7x−x2+10x+3

=2x2+7x+−x2+10x+3

Combine Like Terms:

=2x2+7x+−x2+10x+3

=(2x2+−x2)+(7x+10x)+(3)

=x2+17x+3

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Can you show 7.09 and 7.2 on a number line
Arada [10]
Well 7.09 is on the left side and 7.2 is on the right side
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If you can mow 1000 square feet per minute, how long to mow a circle with diameter of 800 feet?
maria [59]

Answer:

You can calculate the area of the circle

We know the formula is: \pi*r^2

And if diammeter is 800, then the radio is a half: 400

We replace:

\pi*r^2 --> \pi * 400^2 \approx 502654.8  feet

So now we can divide:

502654/1000 = 502,654 minutes

3 0
3 years ago
Which is the inverse of the function f(x)= x+3
tatuchka [14]
Answer is C
let \: y \:  = x + 3
make \: x \: subject \: of \: the \: formula
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4 0
3 years ago
A random sample of 300 circuits generated 13 defectives.
navik [9.2K]

Answer:

p_v =2*P(z  

If we compare the p value and the significance level given \alpha=0.08 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL reject the null hypothesis, and we can said that at 8% of significance the true proportion of defectives is different from 0.05.  

Step-by-step explanation:

1) Data given and notation n  

n=300 represent the random sample taken

X=13 represent the defectives

\hat p=\frac{13}{300}=0.0433 estimated proportion of defectives

p_o=0.05 is the value that we want to test

\alpha=0.08 represent the significance level

Confidence=92% or 0.92

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 the proportion of defective is different from 0.05.:  

Null hypothesis:p=0.05  

Alternative hypothesis:p \neq 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{0.0433-0.05}{\sqrt{\frac{0.05(1-0.05)}{300}}}=-0.5301  

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=0.08. The next step would be calculate the p value for this test.  

Since is a bilateral test the p value would be:  

p_v =2*P(z  

If we compare the p value and the significance level given \alpha=0.08 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL reject the null hypothesis, and we can said that at 8% of significance the true proportion of defectives is different from 0.05.  

3 0
3 years ago
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