Method for directly carrying out significance difference analysis in electronic experiment record

Abstract

The invention discloses a method for directly carrying out significance difference analysis in electronic experiment records. According to the method, significant difference analysis can be carried out by directly using experimental data input in an electronic experimental record, multiple analysis methods are supported, and a calculation process and an analysis result are automatically written into the electronic experimental record. The method comprises the following steps: inputting experiment original data into an electronic experiment recording system; selecting a significant difference analysis template, and matching dimensions in the template to a data column in the experimental record; selecting a data dimension which needs to be subjected to significance difference analysis; selecting a proper statistical test method and parameters; the system automatically calculates a significant difference result; and generating a chart with a significant difference mark and a calculation process in an electronic experiment record. By means of the method, the data analysis process is simplified, the research efficiency is improved, errors in the data transfer process are reduced, seamless integration of experimental records and data analysis is achieved, visual result display is provided, and interpretation and sharing are facilitated. The method is suitable for various experimental designs and statistical test methods, and has a wide application prospect.

Description

Technical Field

[0001] The invention relates to the intersection of computer science and statistics, and in particular to a significant difference analysis module integrated in an electronic experiment recording system. Background Art

[0002] In scientific research, significant difference analysis is an important statistical method used to determine whether there are significant differences between different experimental groups. Traditionally, researchers need to record data in a lab notebook and then input the data into a specialized statistical software for analysis. This process is cumbersome and error-prone. Although there are some electronic experimental record systems, and electronic experimental records usually provide the entry and storage of experimental raw data and analysis results, there is still a lack of integrated statistical analysis modules. Therefore, when performing significant difference analysis, it is still necessary to perform it in an external tool, and then insert the analysis results into the electronic experimental record in the form of pictures. This method requires operators to switch and transfer data between different systems, and subsequent modifications also need to be performed separately in multiple systems. Summary of the invention

[0003] In order to overcome the above-mentioned technical defects, the present invention provides a method for directly performing significance difference analysis in electronic experimental records, which can directly use the data already entered in the electronic experimental records to quickly perform significance difference analysis without the need for data transmission between multiple systems, thereby improving the work efficiency of experimenters and reducing the risk of errors.

[0004] The present application embodiment provides a method for generating a significant difference analysis in an electronic experimental record, the method comprising:

[0005] Match the columns of the original experimental data recorded in the experimental record to the dimensions of the significant difference analysis template;

[0006] Select the statistical test method and parameters to be used for significant difference analysis, and the dimensions to be analyzed;

[0007] Read the original experimental record data column corresponding to the analysis dimension and perform calculations, and insert the calculation process and result charts into the experimental record.

[0008] In an optional embodiment of the present application, the method further includes:

[0009] The experimental results corresponding to each experiment are divided into multiple modules and recorded in the electronic experimental record respectively, and a unique identifier in the current electronic experimental record is generated for the experimental data corresponding to each module;

[0010] When matching the dimensions of the experimental data column and the significant difference analysis template, a combination of the module identifier and the serial number of the column in the module is used as the identifier of the data source corresponding to the dimension.

[0011] The present invention provides a method for directly performing significant difference analysis in electronic experimental records, and the operation steps are as follows:

[0012] Step S1: Entering raw experimental data into the electronic experimental recording system;

[0013] Step S2: Select a significant difference analysis template and match the dimensions in the template to the data columns in the experimental record;

[0014] Step S3: Select the data dimension that needs to be analyzed for significant differences;

[0015] Step S4: Select appropriate statistical test methods and parameters;

[0016] Step S5: The system automatically calculates the significant difference results;

[0017] Step S6: Generate charts and calculation processes with significant difference marks in the electronic experimental record.

[0018] Compared with the existing process operated by experimenters when performing experimental records and significant difference analysis, the advantages of the present invention are:

[0019] Simplified the data analysis process and improved research efficiency;

[0020] Reduces errors during data transfer;

[0021] The integration of electronic experimental records and data analysis is realized, making the operation smoother;

[0022] The calculation process and result charts are automatically generated in the electronic experimental record.

[0023] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Flow chart of the method of the present invention.

[0025] Figure 2 This is an example of a chart showing the results of a significant difference analysis. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0027] Research has found that when researchers conduct experiments in the laboratory, they need to conduct a large number of experiments every day and record the experimental process and result data under different conditions. According to compliance requirements, these experimental data need to be fully recorded in the experimental records. According to the purpose of the experiment, it is often necessary to conduct a significant difference analysis on the experimental data obtained under different conditions to determine the correspondence between the experimental results and the experimental conditions. The electronic experimental recording system provides a complete experimental data recording method, but the analysis and comparison of the results often require the use of external tools, which requires data transmission between different systems. Not only is the operation cumbersome, but it is also easy to cause errors in the results due to human errors.

[0028] Based on this, an embodiment of the present application provides a method for directly performing significance difference analysis in electronic experiment records, which can directly use the experimental data recorded in the electronic experiment records for analysis, and automatically record the calculation process and the final analysis chart in the electronic experiment records, thereby improving the work accuracy and efficiency of the experimenters.

[0029] See also Figure 1 , Figure 1 A method for directly performing significant difference analysis in electronic experimental records is provided for this embodiment, and the operation flow of one embodiment is as follows:

[0030] Step S1: Entering raw experimental data into the electronic experimental recording system;

[0031] Step S2: Select a significant difference analysis template and match the dimensions in the template to the data columns in the experimental record;

[0032] Step S3: Select the data dimension that needs to be analyzed for significant differences;

[0033] Step S4: Select appropriate statistical test methods and parameters;

[0034] Step S5: The system automatically calculates the significant difference results;

[0035] Step S6: Generate charts and calculation processes with significant difference marks in the electronic experimental record.

[0036] In step S1, the experimental raw data is entered in the form of a two-dimensional table, each column is a set of data, and each row is the actual observation value of each experiment. For example, each column represents a set of data of experiments under specific conditions, and each row in each column is the observation value of experiments in different orders under the conditions.

[0037] In an optional embodiment, the raw data of the experiment is stored in multiple two-dimensional data tables in the electronic experiment record in multiple modules. Exemplarily, experiments conducted at different times are recorded in different modules to ensure the real-time and compliance of the experiment record. Here, a unique identifier is generated inside the electronic experiment record for each module where the data table is located to distinguish data from different modules. Different columns in each module are uniquely identified by the column serial number.

[0038] 0017In step S2, the dimensions of the significance difference analysis template are matched with the experimental data columns in the electronic experimental record to determine the data source corresponding to each dimension. The analysis template determines the presentation form of the final result. Exemplarily, the analysis template can be a unit table or a group table, and the final results presented are a single-dimensional bar chart and a grouped bar chart. When matching an experimental data column to a dimension in the analysis template, it is necessary to first specify the module where the two-dimensional table is located, and then specify the serial number of the column in the two-dimensional table, so as to uniquely identify the data source corresponding to the dimension.

[0039] In steps S3 and S4, the dimensions involved in the analysis and the test methods used need to be specified. Exemplarily, a single sample T test is used. In this case, two dimensions need to be involved in the analysis. In one embodiment, two dimensions are specified for analysis. In another embodiment, multiple pairs of dimensions can be selected to perform multiple significant difference analyses simultaneously.

[0040] See also Figure 2 , Figure 2 The result of the analysis in this example includes the standard error of each dimension and the results of the significant difference analysis of the two groups of dimensions. The result is inserted into the electronic experiment record in the form of a chart, and you can click Modify to directly enter the setting state of the dimension and parameter.

[0041] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for directly performing significant difference analysis in electronic experimental records, characterized in that: The experimental data already entered in the electronic experimental record can be directly used for significant difference analysis, multiple analysis methods are supported, and the calculation process and analysis results are automatically written into the electronic experimental record.

2. A method for directly performing significant difference analysis in electronic experimental records according to claim 1, characterized in that: The following steps are involved: Step S1: Entering raw experimental data into the electronic experimental recording system; Step S2: Select a significant difference analysis template and match the dimensions in the template to the data columns in the experimental record; Step S3: Select the data dimension that needs to be analyzed for significant differences; Step S4: Select appropriate statistical test methods and parameters; Step S5: The system automatically calculates the significant difference results; Step S6: Generate charts and calculation processes with significant difference marks in the electronic experimental record.

3. A method for directly performing significant difference analysis in electronic experimental records according to claim 1, characterized in that: The statistical test methods include t-test, variance analysis and non-parametric test.

4. The method for directly performing significant difference analysis in electronic experimental records according to claim 1, characterized in that: The chart with significant difference marks includes mean, standard deviation, p value information, and uses letter marks to show the significance of the difference between groups.

5. A method for directly performing significant difference analysis in electronic experimental records according to any one of claims 1 to 4, characterized in that: The method is implemented by using an electronic experiment recording system.

Images