About data scale classification and basic statistics

This article explores data scale classification and basic statistics.

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Today we will learn about data scale classification and basic statistics.

Measures of data are distinguished by how the data is measured, and basic statistics are used to summarize and describe the characteristics of the data.

Below is information on data scale and basic statistics.

Classification of scale of data

Nominal Scale

This data is classified into categories and has no meaning in order or size.

Examples include gender, blood type, etc.

Ordinal Scale

Data that has a relative order or ranking between data.

Examples include grades, survey responses, etc.

Interval Scale

Data in which the relative size and spacing between data have meaning, such as temperature and year.

The 0 point is chosen arbitrarily and has the characteristic that only relative size differences are valid.

Ratio Scale

This is data with an absolute zero point, and the ratio, relative size, and interval all have meaning.

Examples include length, weight, time, etc.

Basic statistics

Mean

It is the sum of the data divided by the number and indicates the central tendency of the data.

Median

When data are listed in order of size, it is the value in the center position and indicates the central tendency of the data.

Mode

The most frequently occurring value, indicating the central tendency of categorical data.

Standard Deviation

A measure of how spread out the data is from the mean, indicating the variability of the data.

Range

The difference between the maximum and minimum values ​​roughly represents the distribution of the data.

Quartiles

When the data is sorted in order of size, it indicates the values ​​corresponding to 25%, 50%, and 75% and is used to understand the distribution of the data.

Conclusion

Data scale and basic statistics are important concepts for understanding and summarizing data, and are used to identify and analyze data characteristics.

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