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konstantin123 [22]
3 years ago
5

Describe the transformation that takes f(x)=x+1 to g(x) = -x+4. Will Mark Brainliest.​

Mathematics
1 answer:
lions [1.4K]3 years ago
6 0

Answer:

Reflection across y axis

Translate up by 3 units

Step-by-step explanation:

Given

f(x) = x + 1

g(x) = -x + 4

Required

Describe the transformation from f(x) to g(x)

First, take a reflection of f(x) across the y axis.

So f(x) becomes f(-x)

f(x) = x + 1 when reflected

f(-x) = -x +1

Next, translate f(-x) up by 3 units to give g(x)

g(x) = f(-x) + k

Where

k = 3

f(-x) = -x +1

g(x) = -x + 1 + 3

g(x) = -x + 4

Hence, the transformation from f(x) to g(x) includes:

Reflection across y axis

Translate up by 3 units

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Given f(x) = -3x + 5, find f(-6).
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Answer:

23

Step-by-step explanation:

Since it says f(x) that means that when we see f(-6) we are substituting x for -6.

This means that the equation will become

f(-6) = -3(-6) + 5

First multiply -3 and -6 (18)

f(-6) = 18 + 5

Next add 18 and 5 (23)

This means that f(-6) = 23

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y=5x-8

Step-by-step explanation:

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Answer:

p_v =P(z>2.652)=0.0040  

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 defectives is significantly higher than 0.04.  

Step-by-step explanation:

1) Data given and notation  

n=300 represent the random sample taken

X=21 represent the number of defectives (value assumed)

\hat p=\frac{21}{300}=0.07 estimated proportion of defectives

p_o=0.04 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 the proportion of defectives it's higher than 0.04.:  

Null hypothesis:p\leq 0.04  

Alternative hypothesis:p > 0.04  

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{0.07 -0.04}{\sqrt{\frac{0.04(1-0.04)}{300}}}=2.652  

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 right tailed test the p value would be:  

p_v =P(z>2.652)=0.0040  

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 defectives is significantly higher than 0.04.  

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Step-by-step explanation:

<h3>Solved in the attachment!! </h3>

<h3>Hope it helps you!! </h3>

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