Answer:
The answer is "
"
Explanation:
Calculating the mean for brand A:
Calculating the Variance for brand A:
Calculating the Standard deviation:
Calculating the Mean for brand B:
Calculating the Variance for brand B:
Calculating the Standard deviation:
#include using namespace std;int main(){int year = 12,value = 10,total = 0;do{year++;value *= 2;total += value;}while(value*2 < 1000);cout << "Age: " << year << endl;cout << "Last gift: " << value << endl;cout << "Total: " << total << endl;cin.get();return 0;
I think it’s when the party answers
Answer:
It would be correct to say that out-of-order makes a machine's performance more sensitive to branch prediction accuracy.
Explanation:
This can be explained as when a machine is out-of-order, in that state the execution holds importance in prediction accuracy, any increase in these results in rate of prediction near about 25% for the single-issue operating in-order. This is due to the reason that some of the predictions are required for the global pattern history. Most recent outcomes are recorded in the register and for a 4-way machine which is out-of-order, accuracy is very poor as a result of the delay of the branch history for next prediction.
