Final answer:
Suspected outliers in a Tukey boxplot are those values beyond the whiskers, which can be identified by using 1.5 times the IQR beyond the first and third quartiles. To handle outliers, they should be carefully examined for errors or recorded as part of natural variation.
Step-by-step explanation:
Values considered suspected outliers in a Tukey boxplot are a) Those beyond the whiskers. To identify whether there are any outliers, you would use the interquartile range (IQR). The IQR is the difference between the third quartile (Q3) and the first quartile (Q1), which represents the spread of the middle 50 percent of the data. Suspected outliers are values that are either more than 1.5 × IQR above the third quartile or less than 1.5 × IQR below the first quartile.
If a data value is identified as an outlier, it should be examined to determine if it resulted from a data entry error, measurement error, or is a legitimate variation. In some cases, outliers may be removed or handled separately in analysis to prevent them from having an unduly large influence on the results.
For the given data set, with numbers 3, 4, 5, 7, and 9, the IQR is calculated as 7 minus 3, resulting in 4. To check for outliers, you would calculate 1.5 × IQR, which is 6 in this case, and then add it to Q3 (9) to get the upper bound and subtract it from Q1 (3) to get the lower bound. Any number beyond these bounds would be considered a suspected outlier.