Step-by-step explanation:

First, let's move the
to the right-hand side so we can determine what constant we'll need on the left-hand side to complete the square:

From here, since the coefficient of the
term is
, we know the square will be
(since
it's half of
).
To complete this square, we will need to add
to both sides of the equation:



Now we can take the square root of both sides to figure out the solutions to
:


10/8 = 1.25 oz.
there are 8 ounces in 1/2 of a pound. if you divide 8 by 10 bags it equals 1.25 ounces in each bag
Answer:
(2x + 3)(x - 7)
Step-by-step explanation:
Looks like a badly encoded/decoded symbol. It's supposed to be a minus sign, so you're asked to find the expectation of 2<em>X </em>² - <em>Y</em>.
If you don't know how <em>X</em> or <em>Y</em> are distributed, but you know E[<em>X</em> ²] and E[<em>Y</em>], then it's as simple as distributing the expectation over the sum:
E[2<em>X </em>² - <em>Y</em>] = 2 E[<em>X </em>²] - E[<em>Y</em>]
Or, if you're given the expectation and variance of <em>X</em>, you have
Var[<em>X</em>] = E[<em>X</em> ²] - E[<em>X</em>]²
→ E[2<em>X </em>² - <em>Y</em>] = 2 (Var[<em>X</em>] + E[<em>X</em>]²) - E[<em>Y</em>]
Otherwise, you may be given the density function, or joint density, in which case you can determine the expectations by computing an integral or sum.
Answer:
$185 per person
Step-by-step explanation:
22,200/120=185