Answer:
, ](https://tex.z-dn.net/?f=%5B16%20%2B%20%28-18%29%5D%28-4%29)
Step-by-step explanation:
Given: The low temperature on Monday was 16°F. The low temperature on Tuesday was 18°F cooler. The low temperature on Wednesday was –4 times Tuesday’s temperature.
To find: expression that can be used to describe the low temperature on Wednesday
Solution:
Temperature on Monday = 16°F
So,
Temperature on Tuesday = 
Temperature on Wednesday = 
So, expression
can be used to describe the low temperature on Wednesday.
Also,
\,\,\left \{\because (a-b)=\left [ a+(-b) \right ] \right \}](https://tex.z-dn.net/?f=%2816-18%29%28-4%29%3D%5B16%20%2B%20%28-18%29%5D%28-4%29%5C%2C%5C%2C%5Cleft%20%5C%7B%5Cbecause%20%20%28a-b%29%3D%5Cleft%20%5B%20a%2B%28-b%29%20%5Cright%20%5D%20%5Cright%20%5C%7D)
So, expression
also represent temperature on Wednesday.
Answer: 6) 35 meters 7) Ф = 10°
<u>Step-by-step explanation:</u>


Answer:$89.00
Step-by-step explanation:22 times 2 is 44.
15 times 3 is 45.
44 plus 45 is 89
Answer:
it's 0
Step-by-step explanation:
Simplify 3√a0x2√15
3√1*0*x*2√1*5
apply radical rule √a√a=a
√1√1=1
=3.0.2.1.5x
=0
Answer:

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

And replacing we got:

The variance is calculated with this formula:
![Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20E%28X%5E2%29%20-%5BE%28X%29%5D%5E2%20%3D%200.33%20-%280.15%29%5E2%20%3D%200.3075)
And the standard deviation is just the square root of the variance and we got:

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:

And replacing we got:

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

And replacing we got:

The variance is calculated with this formula:
![Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075](https://tex.z-dn.net/?f=%20Var%28X%29%20%3D%20E%28X%5E2%29%20-%5BE%28X%29%5D%5E2%20%3D%200.33%20-%280.15%29%5E2%20%3D%200.3075)
And the standard deviation is just the square root of the variance and we got:
