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skelet666 [1.2K]
3 years ago
5

Find the missing side

Mathematics
1 answer:
Firdavs [7]3 years ago
8 0

\huge\mathbb{\red A \pink{N}\purple{S} \blue{W} \orange{ER}}

\sin(55)  =  \frac{19}{x}  \\  \frac{ \sqrt{3} }{2}  =  \frac{19}{x}  \\ x =  \frac{19 \times 2 \times  \sqrt{3} }{3}  \\ x = 21.9 = 22 \:  \:  \: cm

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X=q+5

Step-by-step explanation:

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A sphere has a radius of 2 inches what is the volume of the sphere nearest tenth?
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A salesman for a new manufacturer of cellular phones claims not only that they cost the retailer less but also that the percenta
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Answer:

z=\frac{0.094-0.04}{\sqrt{0.0642(1-0.0642)(\frac{1}{180}+\frac{1}{225})}}=2.203    

p_v =P(Z>2.203)= 0.0138    

Comparing the p value with the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so then the claim from the retailer makes sense at 1% of significance.  

Step-by-step explanation:

Use a significance level of α=0.01 for the test.

Data given and notation    

X_{1}=17 represent the number of defectives from the retailer

X_{2}=9 represent the number of defectives from the competitor

n_{1}=180 sample 1 selected  

n_{2}=225 sample 2 selected  

p_{1}=\frac{17}{180}=0.094 represent the proportion estimated for defectives from the retailer

p_{2}=\frac{9}{225}=0.04 represent the proportion estimated for defectives from the competitor

\hat p represent the pooled estimate of p

z would represent the statistic (variable of interest)    

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

\alpha=0.01 significance level given  

Concepts and formulas to use    

We need to conduct a hypothesis in order to check if the percentage of defective cellular phones found among his products, ( p1), will be no higher than the percentage of defectives found in a competitor's line, ( p2), the system of hypothesis would be:    

Null hypothesis:p_{1} \leq p_{2}    

Alternative hypothesis:p_{1} > 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{17+9}{180+225}=0.0642  

z-test: Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other.    

Calculate the statistic  

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

z=\frac{0.094-0.04}{\sqrt{0.0642(1-0.0642)(\frac{1}{180}+\frac{1}{225})}}=2.203    

Statistical decision  

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

p_v =P(Z>2.203)= 0.0138    

Comparing the p value with the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so then the claim from the retailer makes sense at 1% of significance.  

5 0
3 years ago
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