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frosja888 [35]
3 years ago
13

Ethanol fuel mixtures have "E" numbers that indicate the percentage of ethanol in the mixture by volume. For example, E10 is a m

ixture of 10% ethanol and 90% gasoline. How much E5 should be mixed with 6000 gal of E10 to make an E9 mixture?
Mathematics
1 answer:
liberstina [14]3 years ago
8 0

According to the problem we start with 6000 gal of E10 which means there is 10% of ethanol  in this 6000, with ths information we can calculate the amount of ethanol already in the mixture:

6000gal*0.1=600gal

The relationship between ethanol and total fluid can be represented like this:

\frac{600}{6000} =0.1

Based on this relationship we can build the one that we are looking for:

E9=9Ethanol91Gasoline=\frac{Ethanol}{Total}=0.09

\frac{TotalEthanol}{TotalSolution} =0.09

the total solution will be:

TotalSolution=6000+X

where X is the E5 solution volume

and the TotalEthanol would be:

TotalEthanol=600+E5Ethanol

where E5ethanol (5% Ethanol 95% Gasoline) would be:

\frac{E5Ethanol}{X}=0.05\\E5Ethanol=0.05X

Now replacing in the relationship we found before:

\frac{600+0.05X}{6000+X}=0.09

Solving for X:

600+0.05X=0.09(6000+X)\\600+0.05X=540+0.09X\\0.09X-0.05=600-540\\0.04X=60\\X=\frac{60}{0.04} \\X=1500

We should mix 1500 gal of E5 to make an E9 mixture

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A worn out bottling machine does not properly apply caps to 5% of the bottles it fills. If you randomly select 20 bottles from t
guajiro [1.7K]

Probability would been equal to 0.9841 if we randomly select 20 bottles it fills.

<h3>What is Probability ?</h3>

The ratio of good outcomes to all possible outcomes of an event is known as the probability. The number of the  positive results for the experiment with 'n' outcomes can also be represented by the symbol x. The probability of an event can be calculated using the following formula.

Probability(Event) = Positive Results/Total Results = x/n

Given,

n = 20

p = 0.05

Thia information gives information about binomial distribution with parameter n = 20 , p = 0.05

Let X be the number of bottles have caps that she not properly applied

    X∝ B( n=20 , p= 0.05)

The p.m.f of X is

P( X=0)= (\frac{20}{x}) ( 0.05)ˣ (1 - 0.05)²⁰ ⁻ˣ

                                                       ; x = 0 , 1, 2.......20

                                                         0 < p < 1

                                                         q= 1 - p

= 0                                                    ; otherwise

P {x ≤ 3} = P { X = 0 } + P{ x= 1 } + P { x= 2 } + P { x= 3}

P( X=0)= (\frac{20}{0}) ( 0.05)⁰ (1 - 0.05)²⁰ ⁻⁰  = 0.3585

P( X = 1)= 0.3774

P( X= 2) = 0.1887

P( X= 3) = 0.0596

                = 0.3585+ 0.3774 +  0.1887+ 0.0596

                 = 0.9841

To know more about Probability, Visit:

brainly.com/question/11234923

#SPJ4

6 0
1 year ago
. You are interested in the amount of time teenagers spend weekly working at part-time jobs. A random sample of 15 teenagers was
agasfer [191]

Answer:

t=\frac{147.3-120}{\frac{50}{\sqrt{15}}}=2.115    

Now we can calculate the degrees of freedom

df=n-1=15-1=14  

If we find a critical value in the t distribution with 14 degrees of freedom who accumulates 0.05 of the area in the right we got t_{critc}= 1.761

Since the calculated value is higher than the critical value we have enough evidence to conclude that the true mean is significantly higher than 120 minutes for the average time of part time jobs

Step-by-step explanation:

Information given

\bar X=147.3 represent the sample mean for the amount of time spent at part time jobs

s=50 represent the sample standard deviation

n=15 sample size  

\mu_o =120 represent the value to check

\alpha=0.05 represent the significance level

t would represent the statistic

p_v represent the p value for the test

System of hypothesis

We want to analyze if the true mean for the amount of time spent at part time jobs is higher than 120, the system of hypothesis would be:  

Null hypothesis:\mu \leq 120  

Alternative hypothesis:\mu > 120  

Since we don't know the population deviation the statistic is given by:

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

Replacing the info given we got:

t=\frac{147.3-120}{\frac{50}{\sqrt{15}}}=2.115    

Now we can calculate the degrees of freedom

df=n-1=15-1=14  

If we find a critical value in the t distribution with 14 degrees of freedom who accumulates 0.05 of the area in the right we got t_{critc}= 1.761

Since the calculated value is higher than the critical value we have enough evidence to conclude that the true mean is significantly higher than 120 minutes for the average time of part time jobs

4 0
3 years ago
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