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AnnyKZ [126]
3 years ago
7

The highway fuel economy of a 2016 Lexus RX 350 FWD 6-cylinder 3.5-L automatic 5-speed using premium fuel is a normally distribu

ted random variable with a mean of μ = 20.50 mpg and a standard deviation of σ = 3.00 mpg. (a) What is the standard error of X¯¯¯X¯ , the mean from a random sample of 36 fill-ups by one driver? (Round your answer to 4 decimal places.) Standard error of X¯¯¯X¯ (b) Within what interval would you expect the sample mean to fall, with 99 percent probability? (Round your answers to 4 decimal places.) The interval is from to
Mathematics
1 answer:
Elodia [21]3 years ago
4 0

Answer:

a) Standard error = 0.5

b) 99% Confidence interval:  (19.2125,21.7875)

Step-by-step explanation:

We are given the following in the question:

Population mean =  20.50 mpg

Sample standard deviation = 3.00 mpg

Sample size , n = 36

Standard Error =

=\displaystyle\frac{\sigma}{\sqrt{n}} = \frac{3}{\sqrt{36}} = 0.5

99% Confidence interval:

\mu \pm z_{critical}\frac{\sigma}{\sqrt{n}}

Putting the values, we get,

z_{critical}\text{ at}~\alpha_{0.01} = \pm 2.575

20.50 \pm 2.575(\displaystyle\frac{3}{\sqrt{36}})= 20.50 \pm 1.2875 = (19.2125,21.7875)

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Digiron [165]

Answer:

2.25 or 2 1/4 pounds

Step-by-step explanation:

if you add them all up (I converted them to decimals when adding) you get 13.5 or 13 1/2 if your using fractions, then you divide that by 6 because thats how many jars there are and you get 2.25 or 2 1/4

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nasty-shy [4]
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3 years ago
A tank can be filled by one pump in 3.2 hours and by another pump in 80 minutes. A third pump can drain the tank in 2 hours and
Mademuasel [1]

Answer:

Rounding to the nearest minute, it would take 95 minutes, or 1 hour and 35 minutes.

Step-by-step explanation:

Let's convert each time to minutes:

3.2 hours = 192 minutes

80 minutes = 80 minutes

2 hr 20 min = 140 minutes

Next, let's find the least common multiple:

LCM(192, 80, 140) = 6720

So let's say the volume of the tank is 6720 units.  The speed of each pump is therefore:

Pump 1 = 6720 units / 192 minutes = 35 units/minute

Pump 2 = 6720 units / 80 minutes = 84 units/minute

Pump 3 = -6720 units / 140 minutes = -48 units/minute

Their combined speed is:

35 + 84 − 48 = 71 units/minute

So the time to fill the tank is:

6720 units / (71 units/minute) = 94.65 minutes

Rounding to the nearest minute, it would take 95 minutes, or 1 hour and 35 minutes.

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In a study of 420,095 Danish cell phone users, 135 subjects developed cancer of the brain or nervous system (based on data from
Maksim231197 [3]

Answer:

z=\frac{0.0003214 -0.00034}{\sqrt{\frac{0.00034(1-0.00034)}{420095}}}=-0.654  

p_v =2*P(Z  

So the p value obtained was a very high value and using the significance level given \alpha=0.005 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say that the true proportion not differs significantly from the specified value of 0.00034 or 0.034%.

Step-by-step explanation:

1) Data given and notation  

n=420095 represent the random sample taken

X=135 represent the subjects developed cancer of the brain or nervous system (based on data from the Journal of the National Cancer Institute as reported in USA Today)

\hat p=\frac{135}{420095}=0.0003214 estimated proportion of subjects developed cancer of the brain or nervous system (based on data from the Journal of the National Cancer Institute as reported in USA Today)

p_o=0.00034 is the value that we want to test

\alpha=0.005 represent the significance level

Confidence=99.5% or 0.995

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 brain or nervous system at a rate that is different from the rate of 0.0340% :  

Null hypothesis:p=0.00034  

Alternative hypothesis:p \neq 0.00034  

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{0.0003214 -0.00034}{\sqrt{\frac{0.00034(1-0.00034)}{420095}}}=-0.654  

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 significance level provided \alpha=0.005. 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 the p value obtained was a very high value and using the significance level given \alpha=0.005 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say that the true proportion not differs significantly from the specified value of 0.00034 or 0.034%.  

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3 years ago
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