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umka2103 [35]
3 years ago
8

The first figure of the Sierpinski

Mathematics
2 answers:
inysia [295]3 years ago
6 0

Answer:

9841

Step-by-step explanation:

Each time the number of shaded triangles is multiplied by 3.  So this is a geometric series:

an = 1 (3)ⁿ⁻¹

The sum of the first n terms of a geometric series is:

S = a₁ (1 - rⁿ) / (1 - r)

Here, a₁ = 1, r = 3, and n = 9.

S = 1 (1 - 3⁹) / (1 - 3)

S = 9841

PolarNik [594]3 years ago
3 0

Answer:

on e2020 its 1 option

Step-by-step explanation:

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Index and laws<br><br> evaluate <br> A) 55^0<br> B)100^1
lisabon 2012 [21]

Answer:

Step-by-step explanation:

Hey there!

so answer for (A is 1)

Answer for (B is 100)

Thank you have fun!

5 0
3 years ago
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A car is traveling at a steady speed. It travels 1 3/4 miles in 2 1/3 minutes. How far will it travel in 47 minutes? In 1 hour?
aleksandrvk [35]

Answer:

  • Distance in 47 minutes = 0.75 × 47 = 35.25 miles
  • Distance in 1 hour or (60 minutes) = 0.75 × 60 = 45 miles

Step-by-step explanation:

Given that the car is traveling at a steady speed.

Distance traveled in 2 1/3 or 7/3 or (2.33) minutes = 1 3/4 miles

                                                                                 = 7/4 or 1.75 miles

Thus,

distance in 1 minute:  1.75/2.33 = 0.75 miles per minute

Thus,

  • Distance in 47 minutes = 0.75 × 47 = 35.25 miles
  • Distance in 1 hour or (60 minutes) = 0.75 × 60 = 45 miles
7 0
3 years ago
An exponential random variable has a standard deviation of 16. Calculate The probability that it takes on a value &lt; 11. Use 3
antiseptic1488 [7]

Answer:

P(X

And using the cdf we got:

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}, x>0

And 0 for other case. Let X the random variable that represent the random variable of interest and we know that the distribution is given by:

X \sim Exp(\lambda)

We know the variance on this case given by :

Var(X) = \frac{1}{\lambda^2}

So then the deviation is given by:

Sd(X) = \frac{1}{\sqrt{\lambda}}

And if we solve for \lambda we got:

\lambda = (\frac{1}{16})^2 = \frac{1}{256}

The cumulative distribution function for the exponential distribution is given by:

F(x) = 1- e^{-\lambda x}

Solution to the problem

And for this case we want to find this probability:

P(X

And using the cdf we got:

P(X

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3 years ago
Nadia MAKES ANOTHER pizza SHE pUTS CHEESE ON ONE HALF OF THE pizza AND pEppERONI ON THE OTHER HALF. THIS TTIME SHE pUTS BACON ON
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Answer:

1/4

Step-by-step explanation:

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Answer:

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Step-by-step explanation:

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