Question

Which of the following statements is not true?

1.When we edit an imported dataset in R, we are only editing its copy inside R, NOT the original file
2.There are clear, straightforward rules about which outliers to remove and how to do it
3.Trimming is the process of removing a top and bottom percentage of extreme values in X and Y variables
4.Different statisticians may have different rules for identifying outliers, even for the same data set

Answer 1

An outlier is a value that is far from the least squares regression line. When editing an imported dataset in R, you are only editing a copy of the dataset, not the original file. Different statisticians may have different rules for identifying outliers.

Step-by-step explanation:

An outlier is an observed value that is far from the least squares regression line. A rule of thumb is that a point more than two standard deviations of the residuals from its predicted value on the least squares regression line is an outlier.

When editing an imported dataset in R, you are only editing a copy of the dataset inside R, not the original file. Any modifications you make in R will not affect the original file.

Different statisticians may have different rules for identifying outliers, even for the same data set. There are no clear, straightforward rules about which outliers to remove and how to do it. The decision to remove an outlier depends on careful examination, consideration of the data and research question, and the potential impact on the analysis.