Answer:
The running time is quadratic (O(n²) )
Step-by-step explanation:
For the set up, we have a constant running time of C. The, a log-linearsorting is called, thus, its execution time, denoted by T(n), is O(n*log(n)). Then, we call n times a linear iteration, with a running time of an+b, for certain constants a and b, thus, the running time of the algorithm is
C + T(n) + n*(a*n+b) = an²+bn + T + C
Since T(n) is O(n*log(n)) and n² is asymptotically bigger than n*log(n), then the running time of the algorith is quadratic, therefore, it is O(n²).
Answer:A device tests whether each blinker on a car is functioning properly. A company estimates that 2.8% of blinkers that they produce are defective. The device is 98% accurate for blinkers that are functioning properly and 96% accurate for blinkers that are defective. You use the device to test a randomly selected blinker. What is the probability that the test result is correct?
Step-by-step explanation:SRRY had to meme a little bit it's 40%
It would stop at 3y+4>11 because the 3y and 4 are unlike terms and can only be divided or multiplied.
1. Graph: a) positive:x>1
b)negative: x<1
c) increasing : none
d ) decreasing: x ∈ R\ { 1 }
2. a) positive: x < -2
b) negative: x > -2
c) increasing: x ∈ R\ { -2 }
d ) decreasing: none.
3. a) positive: x ∈ R\{ 0 }
b ) negative: none
c ) increasing: x< 0
d ) decreasing: x> 0
Draw your own diagram: in the attachment.
