Response: I believe it is 1,3,4
Detailed explanation:
Answer:
This situation illustrates Extrapolation.
Step-by-step explanation:
Extrapolation involves predicting the future based on the premise that current or historical trends will persist.
This also entails assuming the methodologies employed to gauge past trends will apply in the future.
For instance, consider projections regarding global population.
In this case, the number of Elvis Presley impersonators has risen from 48 at his death in 1977 to 7,328 today. If we estimate that by 2016, one in four individuals will become an Elvis impersonator based on the growth trend, this exemplifies Extrapolation.
Answer:
The height is 11.76 meters.
Step-by-step explanation:
To solve this problem, the following equations are necessary:
The first one relates initial and final velocities, taking into account that gravity is 9.81 m/s² and the time is 0.3 seconds:
Vf = Vo + g * t = Vo + 9.81 * 0.3
Vf = Vo + 2.94 (1)
The second one also connects initial and final velocities, but this time with distance S, which we know to be 5 meters:
Vf² = Vo² + 2 * g * S
Vf² = Vo² + 2 * 9.81 * 5
Vf² = Vo² + 98.1 (2)
We now have two equations with two unknowns. By substituting (1) into (2):
(Vo + 2.943)² = Vo² + 98.1
Vo² + 5.886 * Vo + 8.66 = Vo² + 98.1
Canceling Vo² and rearranging gives us:
Vo = 89.44 / 5.886
Vo = 15.195 m/s
Now using the formula:
Vo² = 2 * g * h
h = Vo² / (2 * g) = (15.195²) / (2 * 9.81) = 11.76 meters
So, the height corresponds to 11.76 meters.
Begin by subtracting 8x from both sides of the inequality.
Answer:
0.8894 represents the likelihood of a negative test result given that the disease is present.
Step-by-step explanation:
We are provided the following in the question:
P(Disco Fever) = P( Disease) =

Thus, we can express:
P(No Disease) =

P(Test Returns Positive with disease present) = 0.99

P( false-positive) = 4%

We need to assess the likelihood of a negative test result when the disease is indeed present, i.e.,
P(test result being negative while disease is present)
According to Bayes's theorem, we can write:

0.8894 is the probability that the test result returns negative when the disease exists.