Does removing an outlier greatly affect the regression equation ? What about removing an infuential point ? explain why or why not ?
2006-10-07 06:12:09 · 4 answers · asked by Bear 1 in Science & Mathematics ➔ Mathematics
Outliers are points that do not follow the pattern of the other points in the dataset. These points typically have y-values that are either much above or below the least squares line. That is, they have large residuals in absolute value.
An influential point is one that will result in a large change in the equation of the least squares line if it is removed from the dataset. These points typically have either very large or very small values of the explanatory variable.
An outlier may not affect the regression equation too much if it's not too far off the pattern of the other data.
Take a look at this web page:http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm
It may be helpful.
2006-10-07 06:24:57 · answer #1 · answered by PatsyBee 4 · 1⤊ 0⤋
An influential point is actually defined to be a point that substantially affects the regression equation.
Removing an outlier may or may not greatly affect the regression equation as well. The more data points there are, the less effect an outlier is likely to have.
2006-10-07 06:23:53 · answer #2 · answered by James L 5 · 0⤊ 0⤋
it might to be sure, remove it and find the regression.
removing an influential point, it's pretty ovbious that if it is influential the regressio will change.
an outlier might be influential if it changes the regression
2006-10-07 06:20:08 · answer #3 · answered by javn 2 · 0⤊ 0⤋
Having taken various college point records classes, i'd have a tendency to question any statistical outcomes published everywhere. there are extra than a number of of vairables that for the main section, records are beside the point in serving as an precise predictor of various something. BB, Raji the fairway Witch
2016-12-26 11:59:33 · answer #4 · answered by ? 3 · 0⤊ 0⤋