Data Trimming Consists of

Multiple Choice

Data trimming consists of

A) removing outliers from the data set prior to analyses.
B) focusing attention on statistically significant findings while ignoring nonsignificant findings.
C) dropping the scores for some participants so that the findings better fit one's predictions.
D) repeatedly conducting different types of statistical tests on a data set until significant results turn up.