Answer:
729 is 3 to the power of 6
Step-by-step explanation:
C. multiplication (the 8 x 9 within the parenthesis)
-- They're losing employees . . . so you know that the line will slope down, and
its slope is negative;
-- They're losing employees at a steady rate . . . so you know that the slope is
the same everywhere on the line; this tells you that the graph is a straight line.
I can see the function right now, but I'll show you how to go through the steps to
find the function. I need to point out that these are steps that you've gone through
many times, but now that the subject pops up in a real-world situation, suddenly
you're running around in circles with your hair on fire screaming "What do I do ?
Somebody give me the answer !".
Just take a look at what has already been handed to you:
0 months . . . 65 employees
1 month . . . . 62 employees
2 months . . . 59 employees
You know three points on the line !
(0, 65) , (1, 62) , and (2, 59) .
For the first point, 'x' happens to be zero, so immediately
you have your y-intercept ! ' b ' = 65 .
You can use any two of the points to find the slope of the line.
You will calculate that the slope is negative-3 . . . which you
might have realized as you read the story, looked at the numbers,
and saw that they are <u>firing 3 employees per month</u>.
("Losing" them doesn't quite capture the true spirit of what is happening.)
So your function ... call it ' W(n) ' . . . Workforce after 'n' months . . .
is <em>W(n) = 65 - 3n</em> .
Answer:
X = 58°
Step-by-step explanation:
105° = (2x -11)°
105° + 11° = 2x
116°= 2x
Divide both sides by 2
X = 58°.
Answer:

And we can use the cumulative distribution function given by:

And for this case we can write the probability like this:

And then the final answer for this case would be 
Step-by-step explanation:
For this case we define our random variable X "price of gasoline for a city in the USA" and we know the distribution is given by:

And for this case the density function is given by:

And we want to calculate the following probability:

And we can use the cumulative distribution function given by:

And for this case we can write the probability like this:

And then the final answer for this case would be 