Answer:ok be how hobrhkihfehgdhdj fuiufiisefif jfkijfjfhhfhfhfhf
Explanation:
Incomplete question. Here's a similar question found in the attachments.
<u>Answer:</u>
<u>General Motors Corp, Chrysler, Ford Motor Company, Toyota Motors sales USA Inc, Nissan North America Inc.</u>
<u>Explanation</u>:
By, using the MS Excel computer software, you would be able to compare the 2016 year-to-date sales through February 2017 year-to-date sales for each manufacturer.
Simply copy the data into the data cells of MS Excel, next use the =sum formula (which should have a minus sign; For example, =SUM (B5 - E5) would give you the difference between the 2016 sales and 2017 sales, only if sales for 2016 is found in column B row 5 and sales for 2017 in column E row 5).
Thus, the results obtained can further be evaluated to determine the manufacturers in the top five with increased sales.
Answer: Rich medium
Explanation: A communication is said to be rich id it provides the services like observing the body language, immediate communication, instant judging of the voice tone etc. These factors are commonly found in the face to face interaction which is considered as the rich source of communication. It is considered as rich medium because it has the capability of receiving the output immediately .
Answer:
void print2(int row) {
for (int i = 0; i < row; i++) {
char ch = 'a';
char print = ch;
for (int j = 0; j <= i; j++) {
cout << print++;
}
cout << endl;
}
}
int count_digits(int num) {
int count = 0;
int temp = num;
while (temp != 0) {
temp = temp / 10;
count++;
}
return (num % count);
}
Explanation:
Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
