Answer:
Step 1: 8 + 16x Step 2: 4(4) + 4(12x) Step 3: 4(4 + 12x) Step 4: Dimensions of the rectangle are 4 and 4 + 12x In which step did the student first make an error and what is the correct step? Step 3; 4 + (4 + 12x) Step 3; 4 + (4 ⋅ 12x) Step 2; 4(2) + 4(4x) Step 2; 4(2) + 4x(2)
Answer:
See below.
Step-by-step explanation:
Total = 110
Let calls on third evening = x
second evening = 4x
first evening = x + 8
=> x + 4x + x + 8 = 110
=> 6x = 102
=> x = 17
First evening = x = 17 calls
Second evening = 4x = 68 calls
Third evening = x + 8 = 25 calls
Answer:
Last one
Step-by-step explanation:
The total distance traveled by the robot from t=0 to t=9 is 1422 units
Integration is a way in which smaller components are brought together in pieces to form a whole. Integration can be used in finding areas, volumes and so on.
Given that the position s(t) at any time t is given by the function:
s(t)=9t²−90t+4
The total distance traveled by the robot from t=0 to t=9 can be gotten by integrating the position function within the limits 0< t < 9
Therefore:
![Total\ distance = \int\limits^9_0 {s(t) \, dt \\\\Total\ distance = \int\limits^9_0 {(9t^2-90t+4) \, dt\\\\Total\ distance = [3t^3-45t+4t]_0^9\\\\Total\ distance=-1422\ units](https://tex.z-dn.net/?f=Total%5C%20distance%20%3D%20%5Cint%5Climits%5E9_0%20%7Bs%28t%29%20%5C%2C%20dt%20%5C%5C%5C%5CTotal%5C%20distance%20%3D%20%5Cint%5Climits%5E9_0%20%7B%289t%5E2-90t%2B4%29%20%5C%2C%20dt%5C%5C%5C%5CTotal%5C%20distance%20%3D%20%5B3t%5E3-45t%2B4t%5D_0%5E9%5C%5C%5C%5CTotal%5C%20distance%3D-1422%5C%20units)
The total distance is 1422 units
Find out more at: brainly.com/question/22008756
Minimizing the sum of the squared deviations around the line is called Least square estimation.
It is given that the sum of squares is around the line.
Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.
To learn more about regression visit: brainly.com/question/14563186
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