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Measures of Central Tendency

Measures of Central Tendency

The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...

What is Central Tendency?

What is Central Tendency?

Descriptive statistics describe or summarize relevant characteristics of a sample and aid in the analysis of data of interest. When analyzing large quantities of data and developing an inference, one needs to identify a value representative of the entire data set. Characteristics such as central tendency, extreme values, range of measurements, or the most repeated value can help better understand the data.
The central tendency is the most conventionally used data characteristic. It is a...

Central Tendency: Analysis

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...

Microsoft Excel: Finding Central Tendency, Skew, and Kurtosis

Microsoft Excel: Finding Central Tendency, Skew, and Kurtosis

Central tendency refers to the central point or typical value of a dataset. It summarizes the data set with a single value that represents the center of its distribution. The three main measures of central tendency are:
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Median: The middle value when the data points are arranged in ascending or descending...

Absolute and Local Extreme Values

Absolute and Local Extreme Values

The highest and lowest values of a function, relative to a reference axis, are known as extreme values. These include absolute maximum and absolute minimum values, which represent the highest and lowest points the function reaches across its entire domain. Within a restricted portion of the function, the highest and lowest values are referred to as local maximum and local minimum values, respectively.Periodic functions, such as sine and cosine, show extreme values at infinitely many points due...

Aggregates Classification

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Related Experiment Video

Updated: Jan 22, 2026

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Published on: April 3, 2014

Recent spatial aggregation tendency of rainfall extremes over India.

Akshaya C Nikumbh^1,2, Arindam Chakraborty^3,4, G S Bhat^1,2

¹Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, 560012, India.

Scientific Reports

|July 18, 2019

Summary

Rainfall extremes over India are increasing in size, not frequency, since 1980. Large-scale extreme rainfall events, covering vast areas, are linked to major floods and have distinct planetary-scale precursors.

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Area of Science:

Climatology
Extreme weather events
Hydrology

Background:

Global reports indicate a rise in extreme rainfall event frequency.
Previous studies defined extreme events at individual grid points, neglecting spatial extent.
Understanding the spatial characteristics of rainfall extremes is crucial for accurate climate projections.

Purpose of the Study:

To investigate the changes in spatial extent of rainfall extremes over India.
To determine if the frequency of spatially collocated extreme rainfall events has changed.
To identify precursors associated with large-scale extreme rainfall events.

Main Methods:

Analysis of ground-based rainfall observations over India during boreal summer (1951-2015).
Definition and analysis of spatially collocated rainfall extremes.
Comparison of characteristics between large-sized and smaller extreme rainfall events.

Main Results:

The average spatial extent of collocated rainfall extremes has significantly increased since 1980.
The frequency of these collocated extreme events has remained unchanged.
Approximately 90% of large-sized events (≥70,000 km²) occurred after 1980.
Large-scale extreme events are linked to significant floods in India and exhibit unique planetary-scale precursors.

Conclusions:

The spatial extent, not just frequency, of rainfall extremes is changing.
Size-dependent physical mechanisms influence extreme rainfall events.
Considering the changing spatial extent is vital for accurate climate trend analysis and future projections.