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ale4655 [162]
3 years ago
7

Five days a week, you carpool with 3 co-workers and take turns driving each week. It is 14 miles from your home to your office.

When you drive the carpool you must go an extra 4 miles to pick up your co-workers. If your car averages 18 miles per gallon, about how many gallons of gas should you save every 4 weeks by carpooling?
Mathematics
2 answers:
rusak2 [61]3 years ago
8 0

Answer:

I will save 21.11 gallons in 4 weeks of car pooling.

Step-by-step explanation:

If i have to go office alone then in 4 weeks i will be driving my car = 2×distance from office to home×number of days = 2×14×(4×5) = 28×20 = 560 km.

Now when i carpool with 3 co-workers then i have to drive my car only for 1 week out of 4 weeks.

Means i will be driving total distance = 2× ( distance form office to home + addition distance to pickup co-workers) × number of days

= 2 × (14+4) × 5= 180 km

Now the distance I drove less in 4 weeks = 560 - 180 = 380 km

My car averages 18 miles per gallon gas.

Therefore amount of gas I saved in 4 weeks = 380/18 = 21.11 gallons

elena55 [62]3 years ago
4 0
She saves 8.8888888 gallons of gas every week by carpooling.
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Answer:

(a) P(X \leq 20) = 0.9319

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We are given that a manufacturer of Christmas light bulbs knows that 10% of these bulbs are defective. It is known that light bulbs are defective independently. A box of 150 bulbs is selected at random.

Firstly, the above situation can be represented through binomial distribution, i.e.;

P(X=r) = \binom{n}{r} p^{r} (1-p)^{2} ;x=0,1,2,3,....

where, n = number of samples taken = 150

            r = number of success

           p = probability of success which in our question is % of bulbs that

                  are defective, i.e. 10%

<em>Now, we can't calculate the required probability using binomial distribution because here n is very large(n > 30), so we will convert this distribution into normal distribution using continuity correction.</em>

So, Let X = No. of defective bulbs in a box

<u>Mean of X</u>, \mu = n \times p = 150 \times 0.10 = 15

<u>Standard deviation of X</u>, \sigma = \sqrt{np(1-p)} = \sqrt{150 \times 0.10 \times (1-0.10)} = 3.7

So, X ~ N(\mu = 15, \sigma^{2} = 3.7^{2})

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                Z = \frac{X-\mu}{\sigma} ~ N(0,1)

(a) Probability that this box will contain at most 20 defective light bulbs is given by = P(X \leq 20) = P(X < 20.5)  ---- using continuity correction

    P(X < 20.5) = P( \frac{X-\mu}{\sigma} < \frac{20.5-15}{3.7} ) = P(Z < 1.49) = 0.9319

(b) Expected number of defective light bulbs found in such boxes, on average is given by = E(X) = n \times p = 150 \times 0.10 = 15.

                                           

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