Answer:
6
Step-by-step explanation:
Answer:
Discarding the influential outlying cases when detected is also known as flagging outliers in a data set, and this is because outliers do not follow the rest of the dataset's pattern. if this outliers are not discarded they would have a negative effect on any model attached to the dataset
Step-by-step explanation:
In a regression class ; If extremely influential outlying cases are detected in a Data set, discarding this influential outlying cases is the right way to go about it
Discarding the influential outlying cases when detected is also known as flagging outliers in a data set, and this is because outliers do not follow the rest of the dataset's pattern. if this outliers are not discarded they would have a negative effect on any model attached to the dataset
Answer:
15.24 millimeters
Step-by-step explanation:
6 * 2.54 = 15.24 mm.
I'd say B. but that's only because I divided the number of times he flipped the coin by the number of sides it has, 2, and came up with 246. The closest number on here to that is 231 or B. I hope I helped.
Answer: I helped LOL
Step-by-step explanation: