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
The answer is 1/5 of the students are blond girls, since 1/3 of 3/5 is 1/5.
Divide 3/5 by 3, which is 1/5.
Hope this helps!
Yes, adding going up one every time, 5,6,7,8
Take $15 and multiply it by 0.05 (this will get you the percent). You should get 0.75. So you add 0.75 to $15 and you should get $15.75
V = length×width ×height
V = 9 × 2 × 3
V = 54 units cubed
