Data Plots Review

Front

What is the Interquartile Range (IQR)?

Back

The Interquartile Range (IQR) is a measure of statistical dispersion, representing the range between the first quartile (Q1) and the third quartile (Q3) in a data set. It is calculated as IQR = Q3 - Q1.

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How do you calculate the Interquartile Range from a data set?

Back

To calculate the IQR, first find the first quartile (Q1) and the third quartile (Q3) of the data set. Then, subtract Q1 from Q3: IQR = Q3 - Q1.

Front

What does the first quartile (Q1) represent in a data set?

Back

The first quartile (Q1) is the value below which 25% of the data points fall. It is the median of the lower half of the data set.

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What does the third quartile (Q3) represent in a data set?

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The third quartile (Q3) is the value below which 75% of the data points fall. It is the median of the upper half of the data set.

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What is the range of a data set?

Back

The range is a measure of dispersion that represents the difference between the maximum and minimum values in a data set. It is calculated as Range = Maximum - Minimum.

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How do you find the median of a data set?

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To find the median, arrange the data points in ascending order. If the number of data points is odd, the median is the middle value. If even, it is the average of the two middle values.

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What is the difference between the first and second quartiles?

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The first quartile (Q1) is the median of the lower half of the data, while the second quartile (Q2) is the overall median of the data set.

Front

What is a box plot?

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A box plot is a graphical representation of a data set that displays the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum values.

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What does a box plot indicate about data distribution?

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A box plot provides a visual summary of the central tendency, variability, and skewness of the data distribution, highlighting outliers and the spread of the data.

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What is an outlier in a data set?

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An outlier is a data point that significantly differs from other observations in the data set. It can affect statistical analyses and visualizations.