Answer:
Discrete
Step-by-step explanation:
A set can simply be defined as a list of values. There are many different types of sets, some are intervals, others are enumerated numbers. Often, a set composed of values that are listed is referred to as a discrete set. Discrete sets can be a list of information, or "isolated points". Knowing this information, the most logical answer to fill in the blank is "discrete".
"If a set is made up of isolated points and can be written as a list, it is called a <u>discrete</u> set."
Answer: m∠ABC = m∠CED; Corresponding Angles Theorem
Step-by-step explanation:
i took the test
<span>mostly collect like terms
use associative property which is
(a+b)+c=a+(b+c)
also -a+b-c=(-a)+(b)+(-c) so you can move them around
and remember that:
you just use a general rule
x+x=2x
x^2+x^2=2x^2
3xy4xy=7xy
3x+4x^2=3x+4x^2
you
can only add like terms( like terms are terms that are same name like x
or y are differnt, and like terms have same power exg x^2 and x^3 and
x^1/2 and such
I will oly put the naswers because I don't have much time
first one: 2a+3b+2c
second one: remember that -(-6c)=+6c so the answer is c-10a-2b
third one: -a-8b-5c
</span>
Answer:
factorisation
Step-by-step explanation:
Answer:
And we can find this probability with this difference:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the amount of cofee shops of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability with this difference: