When using $z$ scores to formally identify extreme values in a dataset, which of the following provides the commonly accepted quantitative definition of an outlier?

If a researcher calculates standardized scores for a dataset and finds that a participant has a $z$ score of $-2.85$, this score should be formally classified as an outlier according to the common quantitative criterion.

A researcher is screening data from a study on reaction times. According to the standard quantitative criterion for outliers (scores falling more than 3 standard deviations from the mean), match each participant's calculated $z$ score to its correct classification.

A researcher is evaluating a dataset of test scores to prioritize which cases should be investigated for potential measurement error. Based on the formal definition of an outlier (scores with a $z$ score beyond $\pm 3.00$), rank these four participants from the highest priority for investigation (the most extreme outlier) to the lowest priority (the most typical score).

Based on the formal quantitative method for identifying outliers, which of the following conditions must a score meet to be classified as an outlier?

According to the formal quantitative definition of an outlier, only scores that fall strictly more than three standard deviations above the mean (i.e., $z > +3.00$) are classified as outliers.

When researchers define outliers as scores with a $z$ score strictly greater than +3.00 or strictly less than -3.00, they are identifying data points that fall more than 3 _____ away from the mean.

A researcher computes $z$ scores for participants in a cognitive task study. Apply the formal outlier criterion (strictly $z < -3.00$ or strictly $z > +3.00$) to match each participant's $z$ score to the correct classification.

A researcher computes $z$ scores for five data points and obtains the following values: $-4.20$, $-3.01$, $-3.00$, $-2.99$, and $+3.05$. Carefully analyzing which values satisfy the formal outlier criterion (strictly $z < -3.00$ or strictly $z > +3.00$), the total number of outliers in this set is _____.

A researcher wants to ensure her outlier-handling procedure is transparent and defensible under peer review. Evaluate the following actions and arrange them in the order that best reflects sound, justifiable research practice when using $z$ scores to define and handle outliers.

Describe the formal, quantitative method for identifying outliers in a dataset using $z$ scores. In your description, specify the exact thresholds used to classify a score as an outlier, and explain what these thresholds represent in terms of the dataset's standard deviation and mean.

Based on the quantitative threshold for outliers using $z$ scores, explain whether the researcher should formally classify this student's sleep duration as an outlier. Justify your decision by explaining what a $z$ score of $-3.12$ means conceptually in relation to the sample mean and standard deviation.

A clinical psychology researcher calculates $z$ scores for anxiety symptom severity in a sample of participants. They obtain the following $z$ scores for three participants: Participant A ($z = -3.00$), Participant B ($z = -3.01$), and Participant C ($z = +2.99$). Apply the formal quantitative outlier criterion to determine which of these participants, if any, have scores that are classified as outliers, and explain why.