Automated Data Processing Apparatus for Statistical Analysis
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Solution Overview
Problem
Analyzing large datasets for statistically significant differences is a labor-intensive and time-consuming process, particularly in fields like eye-movement experiments, where manual methods are inefficient and often fail to guarantee success.
Innovation Solution
A data processing apparatus and method that automatically divides datasets using the yx dividing method, performing statistical analyses on the divided regions to reduce human labor and time, employing a processor to store and process data sets with positive real numbers for efficient data grouping and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual data mining analysis is used to locate regions of interest, then the analysis can be performed with simple tools, but the process is time-consuming and labor-consuming
Solution Approach 1:
The system performs automatic data processing and statistical analysis without requiring manual intervention. The processor automatically divides datasets, performs statistical tests, and generates results, allowing the system to serve itself rather than requiring human operators to perform each analysis step manually
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated computational processing. Instead of researchers manually dividing data and performing statistical tests, a processor executes automated algorithms to perform the same analytical functions, substituting human manual work with machine-based processing
2Ease of manufacture
If manual data mining analysis is used, then the methodology is simple to implement, but it is labor-consuming and does not guarantee success in locating regions of interest
Solution Approach 1:
The automated system independently performs the complete analysis workflow including data division, statistical testing, and result generation without requiring manual guidance, thereby maintaining simplicity while improving success rate through systematic automated execution
Solution Approach 2:
The system automatically adjusts analysis parameters such as significance levels, division methods, and statistical test selections to optimize the detection of regions of interest, thereby improving success rate while maintaining ease of implementation through automated parameter management
3Productivity
If automated yx dividing method is used to divide datasets, then data processing efficiency is improved, but the device complexity increases
Solution Approach 1:
The automated analysis process is segmented into distinct modular steps: data division according to yx method, statistical analysis of divided regions, and result generation. This segmentation allows complex automated processing to be broken down into manageable, independently executable modules that can be implemented systematically
Solution Approach 2:
The processor is designed to perform multiple functions including data division, statistical testing, and result generation within a single integrated system. This multi-functionality achieves high data processing efficiency while containing device complexity by consolidating multiple operations into one universal processing unit
Data Source
AI summary
A data processing apparatus, including at least: a register for storing a data set W; a processor, coupled with the register to divide the data set W into a plurality of groups according to an experimental independent variable set V, |V|≥1; use a dividing method yx, where (x,y) belongs to a dividing parameter set L={(x,y)| both x and y are positive real numbers}, |L|≥1, to divide each of the plurality of groups into a plurality of regions in a space of a dimension determined by an element of a data variable set Q, |Q|≥1; perform a statistical analysis with respect to an element Du of a dependent variable set D on the plurality of regions of each of the groups, where Du∈D and |D|≥1; and output a statistical result set R.