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Classification of Data. Classification is the process of arranging the collected data into classes and to subclasses according to their common characteristics. Classification is the grouping of related facts into classes.
Data classification is the process of organizing data by agreed-on categories. Thoroughly planned classification enables more efficient use and protection of critical data across the organization and contributes to risk management, legal discovery and compliance processes.
Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.
The two main branches of statistics are descriptive statistics and inferential statistics. Both of these are employed in scientific analysis of data and both are equally important for the student of statistics.
Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.
Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from research data and provides different ways to assess the robustness of research outputs.
Functions or Uses of Statistics. (1) Statistics helps in providing a better understanding and exact description of a phenomenon of nature. (2) Statistics helps in the proper and efficient planning of a statistical inquiry in any field of study. (3) Statistics helps in collecting appropriate quantitative data.
Statistics help in providing data as well as tools to analyze the data. Some powerful techniques are index numbers, time series analysis, and also forecasting. These are immensely useful in the analysis of data in economic planning. Further, statistical techniques help in framing planning models too.
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