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cluponka [151]
3 years ago
12

This dot plot is symmetric, and the data set has no extreme values

Mathematics
1 answer:
Lapatulllka [165]3 years ago
4 0

Answer:

Where is the plot?

Step-by-step explanation:

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A manufacturer of nickel-hydrogen batteries randomly selects 100 nickel plates for test cells, cycles them a specified number of
kolezko [41]

Answer:

a) Parameter of interest p representing the true proportion of the plates have blistered.

b) Null hypothesis:p\leq 0.1  

Alternative hypothesis:p > 0.1  

c) z=\frac{0.14 -0.1}{\sqrt{\frac{0.1(1-0.1)}{100}}}=1.33  

d) For this case we need to find a value in the normal standard distribution that accumulates 0.1 of the area in the right tail and for this case is:

z_{critc}= 1.28

e) For this case since our calculated value is higher than the critical value 1.33>1.28 we have enough evidence to reject the null hypothesis and we can conclude that the true proportion is significantly higher than 0.1

f) p_v =P(z>1.33)=0.0917  

If we compare the p value and the significance level given \alpha=0.1 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 10% of significance the true proportion is higher than 0.1 or 10%

Step-by-step explanation:

Data given and notation

n=100 represent the random sample taken

Part a

Parameter of interest p representing the true proportion of the plates have blistered.

X=14 represent the number of the plates have blistered.

\hat p=\frac{14}{100}=0.14 estimated proportion of the plates have blistered.

p_o=0.1 is the value that we want to test

\alpha=0.1 represent the significance level

Confidence=90% or 0.90

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Part b: Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that  more than 10% of all plates blister under such circumstances.:  

Null hypothesis:p\leq 0.1  

Alternative hypothesis:p > 0.1  

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 c: Calculate the statistic  

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

z=\frac{0.14 -0.1}{\sqrt{\frac{0.1(1-0.1)}{100}}}=1.33  

Part d: Rejection region

For this case we need to find a value in the normal standard distribution that accumulates 0.1 of the area in the right tail and for this case is:

z_{critc}= 1.28

Part e

For this case since our calculated value is higher than the critical value 1.33>1.28 we have enough evidence to reject the null hypothesis and we can conclude that the true proportion is significantly higher than 0.1

Part f

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

p_v =P(z>1.33)=0.0917  

If we compare the p value and the significance level given \alpha=0.1 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 10% of significance the true proportion is higher than 0.1 or 10%

7 0
3 years ago
How do you do modeling Equivalent Fractions with Number Lines
vivado [14]

Answer:

2

Step-by-step explanation:2

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2 years ago
Operations with radical expression
lord [1]

Hello from MrBillDoesMath!

Answer:

41 sqrt(3)

Discussion:

My first reaction to the problem was:

sqrt(27) = sqrt ( 3 * 9) = 3 sqrt(3)    and

sqrt(48) = sqrt (3*16)  = 4 sqrt(3).

So...

7 * sqrt(27) +  5 sqrt(48) =

7 * (3 sqrt(3)) + 5 * (4 sqrt(3)) =

21 sqrt(3) + 20 sqrt(3) =

41 sqrt(3)

Regards,  

MrB  

P.S.  I'll be on vacation from Friday, Dec 22 to Jan 2, 2019. Have a Great New Year!


7 0
3 years ago
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