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Solnce55 [7]
2 years ago
9

2 x - 5 + 7 y - 3 = 9 x - 1 - y -8 Solve For X AND Y (SHOW WORK PLEASE)

Mathematics
2 answers:
Aleks04 [339]2 years ago
8 0
  • 2x-5+7y-3=9x-1-y-8
  • 2x+7y-8=9x-y-9
  • 2x-9x-8+9=-y-7y
  • -7x+1=-8y
  • -7x=-8y-1
  • 7x=8y+1
  • x=8y+1/7
Maru [420]2 years ago
3 0

Answer:

\large\boxed{\sf x = \frac{8y+1}{7} }

\large\boxed{\sf x = \frac{7x-1}{8} }

<u>Group the Variable's</u>:

2 x - 5 + 7 y - 3 = 9 x - 1 - y -8

2x -9x + 7y +y = -1 -8 +5 + 3

-7x + 8y = -1

<u><em>From this find x and y</em></u>

<u>For X</u>

-7x + 8y = -1

-7x = -1 -8y

7x = 8y + 1

x = (8y +1)/7

<u>For Y</u>

-7x + 8y = -1

8y = -1 +7x

y = (7x -1)/8

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Step-by-step explanation:

I am not sure what your problem here is.

you understand the inequality signs ?

anyway, to get

6×f(-2) + 3×g(1)

we can calculate every part of the expression separately, and then combine all the results into one final result.

f(-2)

we look at the definition.

into what category is -2 falling ? the one with x<-2, or the one with x>=-2 ?

is -2 < -2 ? no.

is -2 >= -2 ? yes, because -2 = -2. therefore, it is also >= -2.

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again, we look at the definition.

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3 0
2 years ago
in a program designed to help patients stop smoking 232 patients were given sustained care and 84.9% of them were no longer smok
grandymaker [24]

Answer:

z=\frac{0.849 -0.8}{\sqrt{\frac{0.8(1-0.8)}{232}}}=1.869  

p_v =2*P(Z>1.869)=0.0616  

If we compare the p value obtained and the significance level given \alpha=0.05 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults were no longer smoking after one month is not significantly different from 0.8 or 80% .  

Step-by-step explanation:

1) Data given and notation

n=232 represent the random sample taken

X represent the adults were no longer smoking after one month

\hat p=0.849 estimated proportion of adults were no longer smoking after one month

p_o=0.80 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 the true proportion is 0.8.:  

Null hypothesis:p=0.8  

Alternative hypothesis:p \neq 0.8  

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{0.849 -0.8}{\sqrt{\frac{0.8(1-0.8)}{232}}}=1.869  

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 bilateral test the p value would be:  

p_v =2*P(Z>1.869)=0.0616  

If we compare the p value obtained and the significance level given \alpha=0.05 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults were no longer smoking after one month is not significantly different from 0.8 or 80% .  

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3 years ago
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Answer:

Step-by-step explanation:

It's not that clear on my screen

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