The worst average to use often depends on the context, but the mode can be misleading when the data set contains outliers or is multimodal (having multiple peaks). In such cases, the mode may not accurately represent the central tendency of the data. Similarly, using the mean in skewed distributions can also be problematic, as it can be disproportionately affected by extreme values. Therefore, it's essential to choose the average that best represents the data's characteristics.
about 1000 times or so on average.
Nope! It is the WORST! Don't use this site! Nope! It is the WORST! Don't use this site! Nope! It is the WORST! Don't use this site!
All algorithms have a best, worst and average case. Algorithms that always perform in constant time have a best, worst and average of O(1).
you are the worst cook in the world i have the worst headache i have ever had
The worst Yonex badminton racquet is the one you use worst.
Worse- That could have been worse. Worst- That is the worst jacket I've ever seen!
.ooo, Rafael Belliard
The possessive form is: Britain's worst balloonist.
Worst-case analysis is often considered more important than average-case analysis because it provides a guaranteed upper bound on an algorithm's performance, ensuring that it will not exceed a certain time or space complexity regardless of the input. This is crucial for applications where reliability and predictability are essential, such as real-time systems or safety-critical applications. In contrast, average-case analysis can be misleading if the average scenario does not accurately represent typical use cases or if the worst-case scenarios occur frequently. Thus, worst-case analysis helps in making more robust and informed decisions about algorithm selection and resource allocation.
Weed or Tobacco.
Weed or Tobacco.
The mean is used for evenly spread data, and median for skewed data. Not sure when the mode should be used.