Answer:
See below
Step-by-step explanation:
I'll provide an example to help you. Let's say we were solving and we wanted to factor the quadratic on the left side. We can't do that because the factors of -7 don't add up to 5. So we'd have to use the quadratic formula. The quadratic formula is essentially the last resort that will solve all quadratic equations, so it could be seen as a preferred method. But, unless you can factor the quadratic, it's much easier to solve.
Now let's do another one. for example can be written as
and we can easily get
and
as solutions since plugging them into the factors would produce 0 (from the Zero Product Property). If we used the quadratic formula, it would take more time to plug in the variables and solve when we can just simply factor.
Hopefully, this explanation helps you to think of your discussion post!
Answer:
<h2>C. G(x) = (x - 1)² - 3</h2>Step-by-step explanation:
f(x) + n - shift the graph of f(x) n units up
f(x) - n - shift the graph of f(x) n units down
f(x - n) - shift the graph of f(x) n units to the right
f(x + n) - shift the graph of f(x) n units to the left
===================================
Look at the picture.
The graph of F(x) shifted 1 unit to the right and 3 units down.
Therefore the equation of the function G(x) is
Answer:
We can find the individual probabilities:
And replacing we got:
Step-by-step explanation:
Previous concepts
The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".
Solution to the problem
Let X the random variable of interest, on this case we now that:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
And we want to find this probability:
And we can use the complement rule:
We can find the individual probabilities:
And replacing we got: