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Bond [772]
3 years ago
11

Parallel to y+5x=4, through (2,2); slope intercept form

Mathematics
2 answers:
hoa [83]3 years ago
7 0

Answer:

y=-5x+8

Step-by-step explanation:

Darya [45]3 years ago
6 0
Answer:
y=-5x+8

Explanation:
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Consider the linear equation y = 2x - 4. Write an equation in slope-
HACTEHA [7]
Answer: y=2x+14

Explanation:
Y=mx+b
Y= 2x-4
M=2

Y= 2x+b

2 = (2 x -6) + b
2=-12+b
12+2=12+b
-12
14=0+b
14=b

Y=2x+14

4 0
3 years ago
I know how to do this but I just want to spend some points :)
Lunna [17]

Answer:

domain: all real numbers

range: y<-2

Step-by-step explanation:

I think its correct but already know the answer sooo yea

7 0
3 years ago
Area of a triangle with a base length of 4in and a height of 9in
Aleks04 [339]
18 inches sqa-wared. "Nailed it!"
4 \times 9 =  36 \\ 36 \div 2 = 18
4 0
3 years ago
Simplify each expression<br>4sg/-5g<br>and<br>(8 + 7a) + 4
Yanka [14]

\dfrac{4sg}{-5g}=-\dfrac{4}{5}\cdor\dfrac{sg}{g}=-\dfrac{4}{5}s\\\\(8+7a)+4=7a+(8+4)=7a+12

5 0
3 years ago
In a recent​ year, a poll asked 2362 random adult citizens of a large country how they rated economic conditions. In the​ poll,
Harman [31]

Answer:

a) The 99% confidence interval is given by (0.198;0.242).

b) Based on the p value obtained and using the significance level assumed \alpha=0.01 we have p_v>\alpha so we can conclude that we fail to reject the null hypothesis, and we can said that at 1% of significance the proportion of people who are rated with Excellent/Good economy conditions not differs from 0.24. The interval also confirms the conclusion since 0.24 it's inside of the interval calculated.

c) \alpha=0.01

Step-by-step explanation:

<em>Data given and notation   </em>

n=2362 represent the random sample taken

X represent the people who says that  they would watch one of the television shows.

\hat p=\frac{X}{n}=0.22 estimated proportion of people rated as​ Excellent/Good economic conditions.

p_o=0.24 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)  <em> </em>

<em>Concepts and formulas to use   </em>

We need to conduct a hypothesis in order to test the claim that 24% of people are rated with good economic conditions:  

Null hypothesis:p=0.24  

Alternative hypothesis:p \neq 0.24  

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.

Part a: Test the hypothesis

<em>Check for the assumptions that he sample must satisfy in order to apply the test   </em>

a)The random sample needs to be representative: On this case the problem no mention about it but we can assume it.  

b) The sample needs to be large enough

np = 2362x0.22=519.64>10 and n(1-p)=2364*(1-0.22)=1843.92>10

Condition satisfied.

<em>Calculate the statistic</em>  

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

z=\frac{0.22 -0.24}{\sqrt{\frac{0.24(1-0.24)}{2362}}}=-2.28

The confidence interval would be given by:

\hat p \pm z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}

The critical value using \alpha=0.01 and \alpha/2 =0.005 would be z_{\alpha/2}=2.58. Replacing the values given we have:

0.22 - (2.58)\sqrt{\frac{0.22(1-0.22)}{2362}}=0.198

 0.22 + (2.58)\sqrt{\frac{0.22(1-0.22)}{2362}}=0.242

So the 99% confidence interval is given by (0.198;0.242).

Part b

<em>Statistical decision   </em>

P value method or p value approach . "This method consists on 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 is \alpha=0.01. 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  

So based on the p value obtained and using the significance level assumed \alpha=0.01 we have p_v>\alpha so we can conclude that we fail to reject the null hypothesis, and we can said that at 1% of significance the proportion of people who are rated with Excellent/Good economy conditions not differs from 0.24. The interval also confirms the conclusion since 0.24 it's inside of the interval calculated.

Part c

The confidence level assumed was 99%, so then the signficance is given by \alpha=1-confidence=1-0.99=0.01

6 0
3 years ago
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