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disa [49]
3 years ago
11

What is f(3)??????????

Mathematics
1 answer:
AURORKA [14]3 years ago
8 0
<h3><u>Explanation</u></h3>
  • Meaning of f(a)

f(a) means the value of f(x) is ... when x = a. That means if we substitute x = 3, we would get f(3).

f(3) also means the value of f(x) is ... when x = 3.

f(x) can also be defined as y // f(x) = y

  • Find f(3) by graph.

You can find the value of f(x) at specific domain from the graph by looking at x = 3 then look up to where the point or where the graph passes. From the graph, when x = 3 as we look up and the graph passes y-coordinate at 1.

Therefore we can say that when x = 3, y = 1.

<h3><u>Answer</u></h3>

f(3) = 1

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Twenty four over the quantity of 3 x minus two. Find f(−2).
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Answer:

f(-2) = -3

Explanation:

Not sure if those last couple numbers are answer choices, but I'm going to infer that they might be.

Twenty four over the quantity of 3 x minus two in standard form is:

f(x) = <span>24<span>3x−2</span></span>

Since the number in the ( ) = x, plug in for x using f(-2)

<span>24<span>3∗<span>(−2)</span>−2</span></span>

P E {M D} {A S} for where to solve first

Multiply the 3 and (-2):

<span>24<span>−6−2</span></span>

Add -6 and -2:

<span>24<span>−8</span></span>

Divide the rest:

f(-2) = -3

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3 years ago
Jaydee was going to sell all of her stamp collection to buy a video game. After selling half of them she changed her mind. she b
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3 years ago
In the book Essentials of Marketing Research, William R. Dillon, Thomas J. Madden, and Neil H. Firtle discuss a research proposa
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Answer:

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500  

p_v =2*P(Z>0.500)=0.617  

So the p value is a very low value and using any significance level for example \alpha=0.05, 0,1,0.15 always p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.  

Step-by-step explanation:

Data given and notation  

X_{1}=25 represent the number of homeowners who would buy the security system

X_{2}=9 represent the number of renters who would buy the security system

n_{1}=140 sample 1

n_{2}=60 sample 2

p_{1}=\frac{25}{140}=0.179 represent the proportion of homeowners who would buy the security system

p_{2}=\frac{9}{60}= 0.15 represent the proportion of renters who would buy the security system

z would represent the statistic (variable of interest)  

p_v represent the value for the test (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the two proportions differs , the system of hypothesis would be:  

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

We need to apply a z test to compare proportions, and the statistic is given by:  

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)  

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{25+9}{140+60}=0.17  

Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500  

Statistical decision

For this case we don't have a significance level provided \alpha, but we can calculate the p value for this test.    

Since is a two sided test the p value would be:  

p_v =2*P(Z>0.500)=0.617  

So the p value is a very low value and using any significance level for example \alpha=0.05, 0,1,0.15 always p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.  

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