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Lera25 [3.4K]
3 years ago
15

HELPP! Geometry volume practice

Mathematics
1 answer:
GarryVolchara [31]3 years ago
7 0

Answer:

Step-by-step explanation:

the height is 80 m

hope that helps

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Without dividing or listing multiples, how can you tell if 61 is a multiple of 6?
Slav-nsk [51]
You check if it is even and that the sum of the digits is divisible by 3. That's the divisibility rule of 6.
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What is the mean of the data set? 17, 24, 26, 13 *<br> Mark only one oval. <br> 4 <br> 13 <br> 20
labwork [276]

Answer:20

Step-by-step explanation: 17+24+26+13=80

Divide by how many numbers there are. Answer: 20

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How long did it take to reach the bottom of the slope
mafiozo [28]
To solve this we are going to use the kinematic equation for final velocity: V_{f}=V_{i}+at
where
V_{f} is the final velocity
V_{i} is the initial velocity 
a is the acceleration 
t is the time

We know for our problem that the the velocity at the beginning of the slope is  2.0ms^{-1}, so V_{i}=2.0. We also know that the speed ad the bottom of the slope is 20ms^{-1}, so V_{f}=20. We also know that the acceleration is 6ms^{-2}, so a=6. Lets replace those values in our formula and solve for t:
V_{f}=V_{i}+at
20=2+6t
6t=18
t= \frac{18}{3}
t=3 seconds

We can conclude that it takes the roller coaster 3 seconds to reach the bottom of the slope.
3 0
3 years ago
What is 1000+2000+3/4​
Pani-rosa [81]

the answer is 3000.75 (3000 and 3/4)

4 0
3 years ago
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The median of a probability distribution can be defined as the number m such that Upper P (Upper X less than or equals m )equals
Alexxandr [17]

Answer:

tex]M=\beta ln(2)[/tex]

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).

Solution to the problem

For this case we can use the following Theorem:

"If X is a continuos random variable of the exponential distribution with parameter \beta for some \beta \in R >0"

Then the median of X is \beta ln (2)

Proof

Let M the median for the random variable X.

From the definition for the exponential distribution we know the denisty function of X is given by:

f_X (x) = \frac{1}{\beta} e^{-\frac{x}{\beta}}

Since we need the median we can put this equation:

P(X

If we evaluate the integral we got this:

\frac{1}{\beta} \int_0^M e^{- \frac{x}{\beta}}dx =\frac{1}{\beta} [-\beta e^{-\frac{x}{\beta}}] \Big|_0^M

And that's equal to:

1/2 = 1 -e^{- \frac{M}{\beta}}

And if we solve for M we got:

1-e^{- \frac{M}{\beta}} = \frac{1}{2}

e^{- \frac{M}{\beta}}=\frac{1}{2}

If we apply natural log on both sides we got:

-\frac{M}{\beta}=ln(1/2)

And then M=\beta ln(2)

5 0
3 years ago
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