Quartile vs. Tertile: What's the Difference?
Edited by Aimie Carlson || By Harlon Moss || Updated on December 11, 2023
Quartiles divide data into four equal parts; tertiles divide data into three equal parts.
Key Differences
Quartiles are statistical measures that divide a data set into four equal parts, each representing 25% of the distributed data. Tertiles, on the other hand, divide data into three equal segments, with each segment representing approximately 33.3% of the data.
In quartiles, the data is segmented into the lower quartile (25th percentile), the median or second quartile (50th percentile), and the upper quartile (75th percentile). Tertiles divide the data into lower (below 33.3rd percentile), middle (between 33.3rd and 66.6th percentiles), and upper tertiles (above 66.6th percentile).
Quartiles are often used in box plot diagrams to represent the spread and skewness of data. Tertiles, while less common, are used to provide a more generalized view of the data distribution.
Quartile calculations are crucial in financial and economic data analysis, helping to understand income or wealth distribution. Tertiles can be applied in similar contexts but offer a less detailed breakdown of data.
In quartiles, outliers and extremes can be more distinctly identified, especially in the context of the interquartile range. Tertiles provide a broader categorization, which might not be as sensitive to subtle variations in a data set.
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Comparison Chart
Number of Divisions
Divides data into 4 equal parts
Divides data into 3 equal parts
Representation
25%, 50%, 75% percentiles
33.3%, 66.6% percentiles
Common Usage
Used in detailed data analysis
Used for a broader overview of data
Sensitivity to Outliers
More sensitive due to smaller segments
Less sensitive due to larger segments
Visualization
Commonly visualized in box plots
Less commonly represented in graphical forms
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Quartile and Tertile Definitions
Quartile
A quartile is a type of quantile that divides a data set into four equal parts.
The first quartile in our data shows that 25% of students scored below 60.
Tertile
Tertiles are statistical measures used to describe the distribution of data points.
The upper tertile in the income data starts at $70,000.
Quartile
Quartiles help in understanding the spread and central tendency of a data set.
The upper quartile of the company's revenue data is $200,000.
Tertile
Tertiles can be particularly useful in dividing a data set for generalized comparisons.
The first tertile in our demographic study shows a younger age group.
Quartile
Quartiles are used to identify outliers and the interquartile range in a dataset.
Outliers in our experiment were defined as values outside the lower and upper quartiles.
Tertile
Tertiles divide a data set into three equal parts, each representing a third of the data.
The middle tertile of the test scores ranges from 40 to 60.
Quartile
Quartiles are statistical values representing 25%, 50%, and 75% percentiles in a data distribution.
The median, or second quartile, of our survey data is 45.
Tertile
In data analysis, tertiles help in breaking down data into three broader segments.
The lower tertile of the survey responses indicates a lack of satisfaction.
Quartile
In descriptive statistics, quartiles segment data into four quarters for easier analysis.
The lower quartile indicates that 25% of the houses are priced below $300,000.
Tertile
Tertiles are used less frequently than quartiles but provide a simplified view of data distribution.
The median falls within the second tertile of our data set.
Quartile
Any of the groups that result when a frequency distribution is divided into four groups of equal size.
Tertile
(statistics) Either of the two points that divide an ordered distribution into three parts, each containing a third of the population.
Quartile
Any of the values that separate each of these groups.
Tertile
(statistics) Any one of the three groups so divided.
The first tertile results include January through April's revenues.
Quartile
(statistics) Any of the three points that divide an ordered distribution into four parts, each containing a quarter of the population.
Quartile
(statistics) Any one of the four groups so divided.
This school is ranked in the first quartile.
Quartile
Same as Quadrate.
Quartile
(statistics) any of three points that divide an ordered distribution into four parts each containing one quarter of the scores
FAQs
What is a quartile in statistics?
A quartile is a type of quantile that divides a data set into four equal parts, each representing 25% of the data.
How are tertiles different from quartiles?
Tertiles divide a data set into three equal parts, each representing approximately 33.3% of the data, unlike quartiles which divide into four parts.
What is the first quartile?
The first quartile, or lower quartile, is the value below which 25% of the data falls.
Is there a difference in calculating quartiles and tertiles?
The calculation method is similar, but quartiles result in four segments, whereas tertiles result in three.
Are tertiles commonly used in statistics?
Tertiles are less common than quartiles but are used to provide a generalized overview of data distribution.
How do quartiles assist in economic data analysis?
Quartiles can be used to analyze income distribution, wealth distribution, and other economic factors in detail.
Are tertiles useful in market research?
Yes, tertiles can be used in market research to segment data into broad categories for analysis.
What is the use of quartiles in data analysis?
Quartiles are used to understand the spread, skewness, and central tendency of a data set, as well as identify outliers.
How is the second tertile different from the median?
The second tertile is a broader range around the median, often including the median but not specifically the 50th percentile.
Is it necessary to use both quartiles and tertiles in analysis?
It's not necessary; the choice between quartiles and tertiles depends on the level of detail required in the analysis.
Can quartiles help in outlier detection?
Yes, quartiles, especially the interquartile range, are useful in identifying outliers in a data set.
What does the third tertile represent?
The third tertile represents the top one-third of data, above the 66.6th percentile.
Can tertiles be visualized in a graph?
Yes, though less common than quartiles, tertiles can be visualized in various graph forms for data representation.
How does the lower tertile differ from the lower quartile?
The lower tertile represents the bottom one-third of data, while the lower quartile represents the bottom 25%.
Are quartiles relevant in all types of data?
Quartiles are most relevant in numerical, continuous data, where distribution and spread are key factors.
What is the interquartile range?
The interquartile range is the difference between the upper and lower quartiles, representing the middle 50% of the data.
What is the importance of the upper quartile?
The upper quartile shows the value below which 75% of the data falls, useful for understanding the higher end of a data set.
How is the median related to quartiles?
The median is the second quartile, dividing the data set into two equal halves.
Can tertiles provide detailed data analysis?
Tertiles offer a more generalized analysis compared to quartiles, which provide a more detailed view.
Can tertiles be applied in educational data?
Yes, tertiles can be used in educational data to broadly categorize performance or other metrics.
About Author
Written by
Harlon MossHarlon is a seasoned quality moderator and accomplished content writer for Difference Wiki. An alumnus of the prestigious University of California, he earned his degree in Computer Science. Leveraging his academic background, Harlon brings a meticulous and informed perspective to his work, ensuring content accuracy and excellence.
Edited by
Aimie CarlsonAimie Carlson, holding a master's degree in English literature, is a fervent English language enthusiast. She lends her writing talents to Difference Wiki, a prominent website that specializes in comparisons, offering readers insightful analyses that both captivate and inform.
