Measures of Central Tendency
A single number that seeks to represent a set of data by identifying the centre position within that set of data is referred to as a measure of central tendency. As a result, central tendency measures are also known as central location measures. They're classified as summary statistics as well.
The mean, median, and mode are all legitimate measures of central tendency, although some measures of central tendency are more appropriate to use than others depending on the circumstances. The mean, mode, and median will be discussed in detail in the following sections, as well as how to compute them and when they should be utilized.
The mean, median, and mode are all legitimate measures of central tendency, although some measures of central tendency are more appropriate to use than others depending on the circumstances. The mean, mode, and median will be discussed in detail in the following sections, as well as how to compute them and when they should be utilized.
Mean
The average of the datasets.
Mode
The most frequently value in the datasets. If the data have multiple values that occurred the most frequently, we have a multi-modal distribution.
Median
The middle value of an ordered datasets.
The average of the datasets.
Mode
The most frequently value in the datasets. If the data have multiple values that occurred the most frequently, we have a multi-modal distribution.
Median
The middle value of an ordered datasets.
Measures of Dispersion
The measure of dispersion, as the name implies, depicts the data scatterings. It explains how the data differs from one another and provides a clear picture of the data distribution. The measure of dispersion reveals whether the distribution of observations is homogeneous or heterogeneous.
Characteristics of Measures of Dispersion
Characteristics of Measures of Dispersion
- A measure of dispersion should be rigidly defined
- It must be easy to calculate and understand
- Not affected much by the fluctuations of observations
- Based on all observations