Isn't it 6 hoirs with the same temperature.?
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:
Abc is the whole explanation.
0.2 + 0.3 + 0.5 = 1
190 x 0.2/1 = 38
190 x 0.3/1 = 57
190 x 0.5/1 = 95
190
0.2: 0.3: 0.5
38: 57: 95
