Answer:
ferris wheel travel approx = 434.72 ft
Step-by-step explanation:
given data
wheel rotates = 9pi/8 radians
total height of the ferris wheel = 246 ft
solution
we can say here that height of the ferris wheel is same as the diameter of the wheel
and wheel is circular in shape
so we get here first radius of wheel that is
radius = half of diameter ..........................1
put here value and we get
radius = 0.5 × 246
radius = 123 ft
and
wheel travel distance = length of arc by a angle of wheel rotates
so here length of arc will be
arc length = radius × wheel rotates angle .....................2
put here value and we get
arc length = 123 ×
arc length = 434.7178 ft
so ferris wheel travel approx = 434.72 ft
Answer:
We use letters to represent a variable in expressions. I hope this helps!
Step-by-step explanation:
Answer:
D. linear; y = –x – 1
Step-by-step explanation:
Linear; y=-x - 1
The slope is negative since it’s decreasing. So it’s not the first equation. It’s not a quadratic equation because there is no forming U shape for this data. It’s not a exponential function because the slope is not 3 and a exponential function is in the form y=a(b)^x
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Answer:
The correct answer is D) linear; y = –x – 1
Step-by-step explanation:
To find this, use any values in the table and it will produce a true statement. This is how we check to see if a model is correct. See the two examples below for proof.
(4, 5)
y = -x - 1
-5 = -4 - 1
- 5 = -5 (TRUE)
(0, -1)
y = -x - 1
-1 = 0 - 1
-1 = -1 (TRUE)
Answer:
0.4x^3 - xy.
Step-by-step explanation:
2/7x(1.4x^2-3.5y) Distributing the2/7x over the parentheses:
= 2/7 * 1.4 x^3 - 2/7 *3.5xy
= 0.4x^3 - xy
Answer:

And if we find the indidivual probabilities we got:

And replacing 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:
The complement rule is a theorem that provides a connection between the probability of an event and the probability of the complement of the event. Lat A the event of interest and A' the complement. The rule is defined by:
Solution to the problem
Let X the random variable of interest, on this case we now that:
For the first part we want this probability:

And if we find the indidivual probabilities we got:

And replacing we got:
