Melvin plays tennis and swims for a total of 110 minutes every day. He plays tennis 40 minutes more than he swims.

Part A: Write a pair of linear equations to show the relationship between the number of minutes Melvin plays tennis (x) and the number of minutes he swims (y) every day. (5 points)

Part B: How much time does Melvin spend swimming every day? (3 points)

Part C: Is it possible for Melvin to have spent 70 minutes playing tennis every day? Explain your reasoning. (2 points)

A . x = y + 40, where x is time playing tennis in minutes and y is time spent swimming in minutes.

B. Melvin spends 35 minutes of swimming every day.

C. No, Melvin can't spend 70 minutes a day playing tennis.

Step-by-step explanation:

Step 1; It is given that Melvin does both for a total time of 110 minutes. x is the time spent playing tennis and y is the time spent swimming. So

x + y = 110 minutes, take this as equation 1.

It is given that Melvin spends 40 minutes more on tennis than swimming so

x = y + 40, take this as equation 2

Substituting equation 2 in 1, we get,

y + 40 + y = 110,

2y + 40 = 110,

2y = 110 - 40 = 70

y =35

Substitute y = 35 in equation 1

x + 35 = 110,

x = 75.

Step 2; So Melvin spends 35 minutes a day swimming and 75 minutes playing tennis equalling a total of 110 minutes a day.

Step 3; If Melvin spends 70 minutes playing tennis, then he spends 70 - 40 minutes swimming which equals his spending 30 minutes that day swimming. So he spent a total of 70 + 30 minutes that day. So he would have spent 100 minutes that day instead of 110 minutes a day so it wouldn't be possible.

7. 153.86 ft

8. 12.56 ft

9. 78.5 m

10. 379.94 in

11. 132.665 m

12. 12.56 yd

13. 226.865 ft

14. 113.04 ft

15. 63.585 ft

16. 254.34 m

17. 50.24 cm

step-by-step explanation:

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the answer   is 200

step-by-step explanation:

this is a problem about poisson probabilities.   i don't know if you've

already studied poisson distributions, or if you have a place to look

to read more about the subject.  

here's how you can see a poisson distribution coming.   when there are

a lot of events that may happen at any time (or any place), and when

you're counting how many of them happen at a particular time (or a

particular place), and each event is independent of the others, then

the result is a poisson distribution.   this is roughly true for the

chocolate chips; one chip being in a cookie has only a small effect on

the probability that another chip will be in the cookie.

once you know you have a poisson distribution, you know a lot.   there

is only one parameter to a poisson distribution, so if you know the

mean, you know everything.   the form of the distribution is

  probability of n chips = {[e^(-x)]*(x^n)} / (n! )