Answer:
The answer is 7.
Step-by-step explanation:The tenths place is the first number after the decimal. In order to know what happens to the whole number you look at the number after the decimal and if its greater than 5 then goes up if no it stays the same. Ex: 2.5 rounded to the tenths place is 3
A. 7/3
HOPE IT HELLS U!!!!
Answer:
20
Step-by-step explanation:
Work backwards. If -2 x 2= -4 then something plus negative four will equal 16, which is 20.
<span>f(x) = x</span>² <span>+ 12x + 6 </span>→ y = x² + 12x + 6<span>
Let us convert the standard form into vertex form.
1) Complete the squares. Isolate x</span>² and x terms.
<span>y - 6 = x</span>² + 12x
<span>
2) Create the perfect square trinomial. Whatever number is added on one side must also be added on the other side.
y - 6 + 36 = x</span>² + 12x + 36<span>
y + 30 = (x + 6)</span>²
<span>y = (x + 6)</span>² - 30 ← Vertex form
<span>
To check:
y = (x + 6) (x + 6) - 30
y = x</span>² + 6x + 6x + 36 - 30
<span>y = x</span>² + 12x + 6<span>
The zero that could be added to the given function is 36, -36</span>
Answer:
For this case we can use the probability mass function and we got:

Step-by-step explanation:
Previous concepts
A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.
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".
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
Solution to the problem
Let X the random variable of interest, on this case we now that:
For this case we can use the probability mass function and we got:
