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2 years ago

14

3. A car travels 65 miles in one hour. How many miles would the car travel in / an hour?

2 answers:

NeTakaya2 years ago

7 0

Answer:

65

Step-by-step explanation:

If a car drives 65 miles in an hour, they would travel 65 miles in one hour. The equation for this would be 65x, with x representing the number of hours driven.

Blizzard [7]2 years ago

3 0

Answer:

A good way to know how to solve a problem like this is to look at the units. Here we have miles per hour (65 miles/hour) and hours (5 hours) and we want to find X miles. So take a look at the units:

(Miles/hour) * (hours) = miles

So we can just plug in the values…

65 * 5 = 325

Whenever I get confused by a question like this I always try to remember that the word "per" just means divided by. So mph = miles/hour. And from there the algebra is pretty simple.

Another tip, your physics professor will always be tickled if at the end of your answer you list some of the assumptions you made like this: "assuming the car is traveling at a perfectly constant rate without stopping."

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Answer:

$\hat p \sim N( p, \sqrt{\frac{p (1-p)}{n}})$

And we can use the z score formula given by:

$z = \frac{\hat p -\mu_p}{\sigma_p}$

And if we find the parameters we got:

$\mu_p = 0.26$

$\sigma_p = \sqrt{\frac{0.26(1-0.26)}{158}} = 0.0349$

And we can find the z score for the value of 0.4 and we got:

$z = \frac{0.4-0.26}{0.0349}= 4.0119$

And we can find this probability:

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And if we use the normal standard table or excel we got:

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Step-by-step explanation:

For this case we have the following info given:

$p = 0.26$ represent the proportion of the company's orders come from first-time customers

$n=158$ represent the sample size

And we want to find the following probability:

$p(\hat p >0.4)$

And we can use the normal approximation since we have the following two conditions:

1) np = 158*0.26 = 41.08>10

2) n(1-p) = 158*(1-0.26) = 116.92>10

And for this case the distribution for the sample proportion is given by:

$\hat p \sim N( p, \sqrt{\frac{p (1-p)}{n}})$

And we can use the z score formula given by:

$z = \frac{\hat p -\mu_p}{\sigma_p}$

And if we find the parameters we got:

$\mu_p = 0.26$

$\sigma_p = \sqrt{\frac{0.26(1-0.26)}{158}} = 0.0349$

And we can find the z score for the value of 0.4 and we got:

$z = \frac{0.4-0.26}{0.0349}= 4.0119$

And we can find this probability:

$P(z>4.0119) = 1-P(z$

And if we use the normal standard table or excel we got:

$P(z>4.0119) = 1-P(z$

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