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:
b
Step-by-step explanation:
We can’t graph for you here, sorry
P=$17.79-$6.95
P=$10.84
P=$10.84 divide by 0.04
P= 271
Jim ordered 271 prints last month
Answer:
first one is SAS
Step-by-step explanation: