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No matter in the recruitment information, or the daily practical information of chicken soup, you must have heard the word statistical analysis. So what on earth is statistical analysis? What does the specific content include? Today, the editor will use the mind map to introduce you to this term.

What is statistical analysis?

Statistics, as the name implies, is to collect information and then calculate, it is a method and means of quantitative processing of data. Statistical analysis, often refers to the collection of relevant data and classification and calculation, so as to analyze the relevant rules of a process. Statistical analysis is the most critical step in the five stages of statistical design, data collection, collation and summary, statistical analysis and information feedback. If there is no such step or this step is not done enough, it will not be able to play a good role in statistical work. To put it another way, without statistical analysis, statistical work will have no vitality, no development, and no status of statistical work. Therefore, many units require workers to have a certain ability of statistical analysis, from this point we can also see the importance of statistical analysis.

So what are the characteristics of statistical analysis? Statistical analysis has three characteristics: scientific, intuitive and repeatable. Scientific means that the statistical analyst is based on mathematics, he has a procedure that can be followed, not relatively random, and statistical analysis also needs rigorous logical thinking to support. Intuition means that the results of statistical analysis can make some abstract laws more intuitive and can be better understood by us. Repeatability means that the research methods of statistical analysis can be repeated and can be verified.

The main contents of statistical analysis include descriptive statistics and inferred statistics. What is the difference between the two? Descriptive statistics is to sort, classify, simplify or chart the data obtained in the study, so as to describe and summarize the characteristics of the data and the relationship between variables. Inference statistics refers to an important statistical method to determine whether there is a certain relationship between data in the form of probability and to infer the overall characteristics with sample statistics. From this we can see that the former is more inclined to collate the existing data, while the latter is to predict under the existing rules.

The basic steps of statistical analysis are: collecting data, collating data, analyzing data. The stage of data collection generally involves literature retrieval, measurement, field survey, questionnaire and so on. To sort out the data, you need to master some software operation skills, such as: SPSS,Excel and so on. Analysis data refers to the process of drawing conclusions through statistical operation on the basis of collating data, which is the core and key of statistical analysis. Finally, some charts, curves and other intuitive results are presented.

There are advantages and disadvantages in everything, and there are also some limitations in statistical analysis, for example, the conclusions reflected in statistical data may not be comprehensive enough, so the number of individuals in statistics, followed by errors in statistical analysis, because it is a probability event. Therefore, when we know its disadvantages, we will pay more attention to it and make our statistical work more effective.

When learning the relevant knowledge of statistical analysis, the editor also suggests that we can use mind mapping to summarize, to better understand and master. Finally, the editor wishes you all to master the ability of statistical analysis as soon as possible.

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