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3241004551 [841]
3 years ago
7

A square board was attached to a wall. The board was divided by four squares and each square was colored either black or white.

How many possible combinations of such coloring are there, if we cannot rotate the given board? PLEASE HELP QUICK! IM NEW AND I NEED ANSWERES! I HOPE BRAINLY DEOS NOT FAIL ME!
Mathematics
1 answer:
PtichkaEL [24]3 years ago
4 0

Answer:

24 combinations

Step-by-step explanation:

For this problem, you use factorials. Factorials are when you multiply every number below it except zero. So like the factorial of 3 or 3! is 3*2*1 is 6.

Factorials are used to figure out how many combinations there are of something. So for you, we have 4 different quadrants so we write that as 4! (! is the sign for factorials.)

By the way, welcome to brainly.  

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4(9*11/2)
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198+81
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What is the slope? A little bit of help. Due today at 11:59pm.
kotykmax [81]

Answer:

2

Step-by-step explanation:

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From past experience, a company has found that in carton of transistors: 92% contain no defective transistors 3% contain one def
jasenka [17]

Answer:

E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500

In order to find the variance we need to find first the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300

The variance is calculated with this formula:

Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075

And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).  

Solution to the problem

LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X

X         0           1           2         3

P(X)    0.92     0.03    0.03     0.02

We can calculate the expected value with the following formula:

E(X) = \sum_{i=1}^n X_i P(X_i)

And replacing we got:

E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500

In order to find the variance we need to find first the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300

The variance is calculated with this formula:

Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075

And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

8 0
4 years ago
!PLEASE EXPLAIN IT EASY SO I UNDERSTAND IT!
Mariana [72]
$1350-$750=$600
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600/10=$60 increase per year
a) since elliot started with $750 in 2000 and he started working in 2000 that would be his initial fee and every year he increased his fee by $60.
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4 0
3 years ago
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I need help with the function plz!!
mylen [45]

Answer:

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Step-by-step explanation:

Objective:Functions

The table of values range and domain isn't proportional so the answer is exponential.

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ab {}^{x}

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\frac{1}{4}

b=1/4 so plug that in our expression.

a( \frac{1}{4} ) {}^{x}

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a(  \frac{1}{4}  ) {}^{1}  = 512

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So our function is

2048 \times ( \frac{1}{4} ) {}^{x}

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