Consider the graph of function g below. A diagonal curve declines from (negative 1, 9) through (0, 6), (2, 0), (3, negative 3),
(4, negative 6), and (5, negative 9) on an x y coordinate plane. Determine which sequences of transformations could be applied to the parent function f(x) = x to obtain the graph of g. Reflect over the x-axis, vertically stretch by a factor of 3, and then shift up 6 units. Shift right 6 units, reflect over x-axis, and then vertically stretch by a factor of 3. Shift up 6 units, reflect over the x-axis, and then vertically stretch by a factor of 3. Shift right 2 units, reflect over x-axis, and then vertically stretch by a factor of 3. Reflect over the y-axis, vertically stretch by a factor of 3, and then shift up 6 units. Shift left 2 units, reflect over x-axis, and then vertically stretch by a factor of 3.
1 answer:
You might be interested in
Answer:
a) For this case we can find the cumulative distribution function first:
So then by the complement rule we have this:
b)
So then we have this using independence:
We want to find the following probability:
Using the definition of conditional probability we got:
And we see that if a = 2 and b=5 we have:
c) For this case we use independent identical and with the same distribution experiments.
And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.
Step-by-step explanation:
Previous concepts
The geometric distribution represents "the number of failures before you get a success in a series of Bernoulli trials. This discrete probability distribution is represented by the probability density function:"
If we define the random of variable Y we know that:
Part a
For this case we can find the cumulative distribution function first:
So then by the complement rule we have this:
Part b
For this case we can use the result from part a to conclude that:
So then we have this assuming independence:
We want to find the following probability:
Using the definition of conditional probability we got:
And we see that if a = 2 and b=5 we have:
Part c
For this case we use independent identical and with the same distribution experiments.
And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.