well if you really want to know, ASK SOMEONE ELSE 'CUZ I HAVE NO DANG IDEA!!!
The Absolute Measure of dispersion is basically the measure of variation from the mean such as standard deviation. On the other hand the relative measure of dispersion is basically the position of a certain variable with reference to or as compared with the other variables. Such as the percentiles or the z-score.
difference
Measures of dispersion quantify the spread or variability of a dataset. The most common measures include the range, which is the difference between the maximum and minimum values; the variance, which reflects the average squared deviation from the mean; and the standard deviation, the square root of the variance, providing a measure of spread in the same units as the data. Additionally, the interquartile range (IQR) measures the spread of the middle 50% of the data, highlighting the range between the first and third quartiles.
distinguish between dispersion and skewness
Measures of dispersion that do not divide a set of observations into equal parts include the range and the variance. The range is simply the difference between the maximum and minimum values in a dataset, providing insight into the spread but not segmenting the data. Variance measures how far each observation is from the mean but does not create distinct segments of the data like quartiles or percentiles do.
The Absolute Measure of dispersion is basically the measure of variation from the mean such as standard deviation. On the other hand the relative measure of dispersion is basically the position of a certain variable with reference to or as compared with the other variables. Such as the percentiles or the z-score.
Absolute dispersion measures the spread of data points in a dataset without considering their direction. It can be calculated using metrics such as the range, which is the difference between the maximum and minimum values, or the mean absolute deviation (MAD), which is the average of the absolute differences between each data point and the mean of the dataset. These calculations provide insights into the variability and consistency of the data.
difference
Mean Absolute Deviation (MAD) is a statistical measure that quantifies the average absolute differences between each data point in a dataset and the dataset's mean. It provides insight into the variability or dispersion of the data by calculating the average of these absolute differences. MAD is particularly useful because it is less sensitive to outliers compared to other measures of dispersion, such as standard deviation. It is commonly used in fields like finance, quality control, and any area where understanding variability is essential.
Absolute strength measures strength regardless of your body size, while relative strength measures strength adjusted for your weight.
Measures of dispersion quantify the spread or variability of a dataset. The most common measures include the range, which is the difference between the maximum and minimum values; the variance, which reflects the average squared deviation from the mean; and the standard deviation, the square root of the variance, providing a measure of spread in the same units as the data. Additionally, the interquartile range (IQR) measures the spread of the middle 50% of the data, highlighting the range between the first and third quartiles.
distinguish between dispersion and skewness
Measures of central tendency are averages. Range , the difference between the maximum and the minimum, is a measure of dispersion or variation.
Measures of dispersion that do not divide a set of observations into equal parts include the range and the variance. The range is simply the difference between the maximum and minimum values in a dataset, providing insight into the spread but not segmenting the data. Variance measures how far each observation is from the mean but does not create distinct segments of the data like quartiles or percentiles do.
dispersion medium is contained
It's a statistical tool used in psychology. A simple way of calculating the measure of dispersion is to calculate the range. The range is the difference between the smallest and largest value in a set of scores. This is a fairly crude measure of dispersion as any one high or low scale can distort the data. A more sophisticated measure of dispersion is the standard deviation which tells you how much on average scores differ from the mean.
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.