Two rectangular properties share a common side. Lot A is 33 feet wide and 42 feet long.

Mathematics

1 answer:

s344n2d4d5 [400]3 years ago

7 0

Answer:

The width of lot B is 11 feet, so option A is correct.

Step-by-step explanation:

Given:

Two rectangular properties share a common side.

Lot A is 33 feet wide and 42 feet long.

The combined area of the lots = 1,848 square feet.

To find:

How many feet wide is Lot B?

Solution:

we know that, area of a rectangle is length x breadth

Then area of lot A = 33 x 42 = 1386 square feet.

And area of lot B = width x 42

Now, we are given that, total area = 1848

area of lot A + area of lot B = 1848

1386 + width x 42 = 1848

width x 42 = 1848 – 1386

width x 42 = 462

$width =\frac{42}{462}$

width = 11

Hence, the width of lot B is 11 feet, so option A is correct.

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Oil spill spreads 25 m² every 1/6 hour how much area does the oil spill cover after two hours

Delvig [45]

1/6 of an hour is 10 minutes because there are 60 minutes in an hour so 60/6=10
so it's 25m^2/10minutes
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hope this helped

6 0

2 years ago

Read 2 more answers

Data collected at Toronto Pearson International Airport suggests that an exponential distribution with mean value 2725hours is a

Ivan

Answer:

a) What is the probability that the duration of a particular rainfall event at this location is at least 2 hours?

We want this probability"

$P(X >2) = 1-P(X\leq 2) = 1-(1- e^{-0.367 *2})=e^{-0.367 *2}= 0.48$

At most 3 hours?

$P(X \leq 3) = F(3) = 1-e^{-0.367*3}= 1-0.333 =0.667$

b) What is the probability that rainfall duration exceeds the mean value by more than 2 standard deviations?

$P(X > 2.725 + 2*5.540) = P(X>13.62) = 1-P(X$

What is the probability that it is less than the mean value by more than one standard deviation?

$P(X$

Step-by-step explanation:

Previous concepts

The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution". The probability density function is given by:

$P(X=x)=\lambda e^{-\lambda x}$