The parabolic motion is an illustration of a quadratic function
The equation that models that path of the rocket is y = -16/31x^2 + 256/31x - 880/31
<h3>How to model the function?</h3>
Given that:
x stands for time and y stands for height in feet
So, we have the following coordinate points
(x,y) = (5,0), (11,0) and (10,80)
A parabolic motion is represented as:
y =ax^2 + bx + c
At (5,0), we have:
25a + 5b + c = 0
c= -25a - 5b
At (11,0), we have:
121a + 11b + c = 0
Substitute c= -25a - 5b
121a + 11b -25a - 5b = 0
Simpify
96a + 6b = 0
At (10,80), we have:
100a + 10b + c = 80
Substitute c= -25a - 5b
100a + 10b - 25a -5b = 80
75a -5b = 80
Divide through by 5
15a -b = 16
Make b the subject
b = 15a + 16
Substitute b = 15a + 16 in 96a + 6b = 0
96a + 6(15a + 16) = 0
Expand
96a + 90a + 96 = 0
This gives
186a = -96
Solve for a
a = -16/31
Recall that:
b = 15a + 16
So, we have:
b = -15 * 16/31 + 16
b =-240/31 + 16
Take LCM
b =(-240 + 31 * 16)/31
[tex]b =256/31
Also, we have:
c= -25a - 5b
This gives
c= 25*16/31 - 5 * 256/31
Take LCM
c= -880/31
Recall that:
y =ax^2 + bx + c
This gives
y = -16/31x^2 + 256/31x - 880/31
Hence, the equation that models that path of the rocket is y = -16/31x^2 + 256/31x - 880/31
Read more about parabolic motion at:
brainly.com/question/1130127
Answer: C. there is still not enough evidence to conclude that the time series is stationary.
Step-by-step explanation: First thing to note for a time series plot is that it is required to select a suitable forecast method for the data set being considered.
A stationary time series means that the process generating the data set has a constant mean and the variations are constant over time. This means all evidence is present leading to the conclusion that the entire time series is stationary. A stationary time series thus exhibits an horizontal pattern which enables an appropriate forecast method to be selected for this type of pattern.
A horizontal pattern of a time series plot indicates that a data set fluctuates around a constant mean for a period of time. This period of time may however not be the entire time of the time series or take the entire data set into consideration and might just be a reflection of a portion of the time series hence why it can not be explicitly considered to be stationary. This means that a horizontal pattern can change into a seasonal or trending pattern if more variables/data are added over time.
For instance, a manufacturer sells a certain amount of products over a 10 week period and the resulting pattern of a time series plot is horizontal, then from the 11th week to the 15th week he gets a sharp and continuous increase in sales. This change in level will therefore change the time series plot from horizontal to trending making it more difficult to select a suitable forecast method.
Answer:
It's the first option.
Step-by-step explanation:
It is turned down so the one half is negative (-1/2)
parabola will be in the form of a(x-h)^2 + k. (-h, k) is your vertex, in this case that is (15,25). so in the equation, you will have
-1/2(x-15)^2 + 25. first one.
Hope this helps!
Hey There!
Answer:
D. 28
Explanation:
So all you have to do in your answer is evaluate:
-(-28)
= 28
= D. 28
Therefore, that is how you found your answer.
Hope this Helps!
