Understanding Outliers in Data
A Grade 12 Math worksheet focusing on identifying, analyzing, and understanding the impact of outliers in various data sets.
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Understanding Outliers in Data
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Read each question carefully and provide your best answer. Show all your work for calculations.
1. Consider the following data set representing the scores of students on a math test: 78, 82, 85, 88, 90, 92, 95, 100, 30. Calculate the Interquartile Range (IQR) and use the 1.5 IQR rule to identify any outliers in this data set.
2. An outlier is added to a data set. Which of the following statistics is LEAST affected by the presence of an outlier?
Mean
Median
Range
Standard Deviation
3. An outlier can significantly affect the and the of a data set, making them less representative of the typical values. However, the and the are more resistant to the influence of outliers.
4. All extreme values in a data set are considered outliers.
True
False
5. Construct a box plot for the data set: 10, 12, 15, 18, 20, 22, 25, 40. Clearly label the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum values. Identify any outliers based on the 1.5 IQR rule and indicate them on your box plot.
Match the term with its correct definition.
1. Outlier
a. The middle value in an ordered data set.
2. Interquartile Range (IQR)
b. A data point that differs significantly from other observations.
3. Median
c. The range between the first and third quartiles.