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sertanlavr [38]
3 years ago
5

John drives to work each morning and the trip takes an average of µ = 38 minutes. The distribution of driving times is approxima

tely normal with a standard deviation of σ = 5 minutes. For a randomly selected morning, what is the probability that John’s drive to work will take less than 35 minutes?​
Mathematics
1 answer:
exis [7]3 years ago
5 0

Answer:

The probability that John’s drive to work will take less than 35 minutes is 0.2743

Step-by-step explanation:

Given : \mu = 38 \\\sigma = 5

To Find :what is the probability that John’s drive to work will take less than 35 minutes?​

Solution:

\mu = 38 \\\sigma = 5

We are supposed to find P(x<35)

We will use z score

Formula: z=\frac{x-\mu}{\sigma}

Substitute x = 35

z=\frac{35-38}{5}

z= −0.6

Refer the z table for p value

P(x<35)= 0.2743

Hence the probability that John’s drive to work will take less than 35 minutes is 0.2743

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Tain has a great literary tradition that spans centuries. One might assume, then, that Britons read more than citizens of other
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Answer:

Null hypothesis:p_{1} \leq p_{2}  

Alternative hypothesis:p_{1} > p_{2}  

z=3.02  

p_v =P(Z>3.02)=0.00127  

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 so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion of Canadians is not significantly higher than the porportions of readers at Britons.  

Step-by-step explanation:

1) Data given and notation  

X_{1}=0.86*1004 represent the number of Canadians randomly sampled by Gallup that read at least one book in the past year

X_{2}=0.81*1009 represent the number of Britons randomly sampled that read at least one book in the past year

n_{1}=1004 sample of Gallup selected

n_{2}=1009 sample of Britons selected

p_{1}=0.86 represent the proportion of Canadians randomly sampled by Gallup that read at least one book in the past year

p_{2}=0.81 represent the proportion of Britons randomly sampled that read at least one book in the past year

z would represent the statistic (variable of interest)  

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

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the proportion for men with red/green color blindness is a higher than the rate for women  , 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{0.81+0.86}{2}=0.835

3) Calculate the statistic

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

z=\frac{0.86-0.81}{\sqrt{0.835(1-0.835)(\frac{1}{1004}+\frac{1}{1009})}}=3.02  

4) 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 one side test the p value would be:  

p_v =P(Z>3.02)=0.00127  

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 so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion of Canadians is not significantly higher than the porportions of readers at Britons.  

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3 years ago
Use subtraction to check addition problems 391+124=551
son4ous [18]

Answer:

391+124=\=551

Step-by-step explanation:

subtract either the 124 or 391 from both sides.

391=427 which means they are not equal. so it has no solution.

3 0
3 years ago
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