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
0.62068966 or 18/29 depending on how you want to set it up.
Answer: i dont really know if im right but here! :L
Step-by-step explanation: Now, say G is an Abelian group, finitely generated from generator In this sense abelian groups are “more interesting” than vector spaces. and in the table below, the second last column is the identity, while the last column is cyclic of order 4, with 9g the generator
Answer:
- Circumference = 69.14cm
- Area = 380.29cm²
Step-by-step explanation:
Circumference.
Circumference of a circle is calculated by the formula:
= Pie * diameter
= π * diameter
= 22/7 * 22
= 69.14 cm
Area
Area of circle:
= Pie * radius ²
Radius = diameter/2
= 22/2
= 11 cm
Area = 22/7 * 11²
= 22/7 * 121
= 380.29 cm²
