To solve this problem,you need to use the formula d = rd (distance = rates x time)She runs at a speed of 7 mph and walks at a speed of 3 mph. Her distance running is d = 7trwhere tr is the time she spends running Her distance walking isd = 3twwhere tw is the time she spends walking The distances are the same so7tr = 3tw We also know that the total time is 4 hourstr + tw = 4tr = 4-tw Substitute this value of tr in the first equation7tr = 3tw7(4-tw) = 3tw28-7tw = 3tw28 = 10tw2.8 = tw Denise will spend 2.8 hours (2 hours, 48 minutes) walking back and 1.2 hours (1 hour, 12 minutes running.
Hope I helped :)
Answer:
<h2>it will take 30 minutes</h2>
Step-by-step explanation:
obtain a formula
<h3>=> M = $0.10($p)+$25</h3>
<u>insert the value of p dollars</u>
<h3>=> M = $0.10(50) + 25</h3>
<u>multiply 50 by 0.10</u>
<h3>=> M = $5 + 25</h3>
<em> </em><u>add 25 + 5</u>
<h3><em><u>=></u></em> M = $30</h3>
<u>So it takes 30 minutes for international minutes</u> <em><u>Thank </u></em><em><u>You</u></em>
^_^
I dont know sorry i am also bad in math
Answer:
Where
and 
We are interested on this probability

And the best way to solve this problem is using the normal standard distribution and the z score given by:

If we apply this formula to our probability we got this:
And we can find this probability using the complement rule:

Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:
Where
and 
We are interested on this probability

And the best way to solve this problem is using the normal standard distribution and the z score given by:

If we apply this formula to our probability we got this:
And we can find this probability using the complement rule:
