In the field of statistics, data analysis is divided into descriptive statistical analysis, exploratory data analysis and confirmatory data analysis. Exploratory data analysis focuses on discovering new features in data, while confirmatory data analysis focuses on confirming or falsifying existing assumptions.
Exploratory data analysis refers to a method of analyzing data in order to form hypothesis testing, which is a supplement to traditional statistical hypothesis testing.
Extended data
Steps of data analysis
The main activities of data analysis process include identifying information requirements, collecting data, analyzing data, evaluating and improving the effectiveness of data analysis.
1. Determine the requirements
Identifying information requirements is the first condition to ensure the effectiveness of data analysis process, which can provide clear goals for data collection and analysis. It is the manager's responsibility to determine the information needs. Managers should put forward information requirements according to the needs of decision-making and process control.
As far as process control is concerned, managers should identify the information needed to support the evaluation of process input, process output, rationality of resource allocation, optimization scheme of process activities and discovery of abnormal changes in the process.
Step 2 collect data
Collecting data purposefully is the basis to ensure the effectiveness of data analysis process. Organizations need to plan the contents, channels and methods of collecting data from data analysis diagrams. Planning should consider:
1) Convert the identified requirements into specific requirements. For example, when evaluating suppliers, the data to be collected may include relevant data, such as their process capability and uncertainty of measurement system.
2) Determine who collects data when and where, and through what channels and methods.
3) The record sheet should be easy to use. ?
4) Take effective measures to prevent data loss and false data from interfering with the system.
Step 3 analyze the data
Data analysis is to process, sort out and analyze the collected data and turn them into information. Usually, the method is as follows:
Seven old tools, namely pareto chart, Causality Diagram, Analytic Hierarchy Process, Questionnaire, Walking Diagram, Histogram and Control Diagram;
Seven new tools, namely, correlation diagram, system diagram, matrix diagram, KJ method, plan evaluation and review technology, PDPC method and matrix data diagram.
4. Process improvement
Data analysis is the basis of quality management system. When appropriate, the manager of the organization should evaluate its effectiveness by analyzing the following questions:
1) Whether the information provided for decision-making is sufficient and credible, and whether there are problems of insufficient, inaccurate and lagging information leading to decision-making mistakes.
2) Whether the role of information in the quality management system, process and continuous improvement of products is consistent with the expected value, and whether data analysis is effectively used in the product realization process.
3) Whether the purpose of collecting data is clear, whether the collected data is true and sufficient, and whether the information channels are unblocked.
4) Whether the data analysis method is reasonable and whether the risk is controlled within an acceptable range.
5) Whether the resources needed for data analysis are guaranteed.
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