Central tendency will only give you information on the location of the data. You also need dispersion to define the spread of the data. In addition, shape should also be part of the defining criteria of data. So, you need: location, spread & shape as best measures to define data.
Measures of central tendency, such as mean, median, and mode, summarize a dataset by identifying the central point or typical value. In contrast, measures of dispersion, such as range, variance, and standard deviation, describe the spread or variability of the data points around the central value. While central tendency provides an overview of where data points cluster, dispersion indicates how much the data varies, highlighting the degree of diversity or consistency within the dataset. Together, they offer a comprehensive understanding of the data's characteristics.
Because it measures the averages of a collection of data
"Measures of central tendency are statistical measures." is an accurate statement.
well...the measures of the central tendency would be 30 minutes
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Common measures of central tendency are the mean, median, mode. Common measures of dispersion are range, interquartile range, variance, standard deviation.
None. Measures of central tendency are not significantly affected by the spread or dispersion of data.
Measures of central tendency are averages. Range , the difference between the maximum and the minimum, is a measure of dispersion or variation.
There are more than three measures. Some are better than others in some situations but not as good in other situations.
Measures of central tendency, such as mean, median, and mode, summarize a dataset by identifying the central point or typical value. In contrast, measures of dispersion, such as range, variance, and standard deviation, describe the spread or variability of the data points around the central value. While central tendency provides an overview of where data points cluster, dispersion indicates how much the data varies, highlighting the degree of diversity or consistency within the dataset. Together, they offer a comprehensive understanding of the data's characteristics.
The two most important measures of a normal distribution are the mean and the standard deviation. The mean indicates the central tendency or average of the data, while the standard deviation measures the dispersion or spread of the data around the mean. Together, these parameters define the shape and location of the normal distribution curve.
It is the measure of central tendency.
Because it measures the averages of a collection of data
no it is a measure of dispersion.
You calculate summary statistics: measures of the central tendency and dispersion (spread). The precise statistics would depend on the nature of the data set.