Significance Evaluation Program Matrix Table Visualization

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Solution Overview

Problem

Conventional methods for evaluating statistical significance in data from multiple evaluation items are cumbersome and difficult to interpret, especially when dealing with a large number of items, requiring significant time and effort to understand the presence or absence of significance differences and their degrees.

Innovation Solution

A computer-based significance evaluation program that calculates p-values and displays results in a matrix table format, using statistical methods like t-tests and chi-squared tests, with color and hatching indications to easily convey significance information for each evaluation item, allowing for quick recognition of significance and degree of significance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional methods (tables or graphs with p-values) are used to indicate significance evaluation results, then the results can be presented, but it becomes extremely difficult to interpret and grasp the presence/absence of significance difference or degree of significance at a glance, especially when there are a large number of evaluation items

Engineering Contradiction:
Improveinterpretability of significance resultsVSAvoidcomplexity of result presentation
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent applies color changes to indicate significance levels in a matrix table. Different colors represent different significance levels (e.g., red for highly significant, yellow for moderately significant, green for not significant). This allows users to immediately grasp the presence and degree of significance differences without having to read or compare numerical p-values, directly resolving the contradiction between presenting results and making them interpretable.

Inventive Principle:
Principle #32Color changes

2Measurement precision

If p-values are listed for each evaluation item in a table, then the statistical results are recorded, but the listed numerals are not easily understood and it is troublesome to compare the p-values of evaluation items with each other

Engineering Contradiction:
Improvestatistical accuracyVSAvoidease of interpretation
Core Design Contradiction:
Measurement precisionVSEase of operation

Solution Approach 1:

The patent replaces numerical p-values with color-coded indicators in a matrix table. Each cell contains a color that corresponds to a significance level, eliminating the need for users to read, understand, or compare numerical values. This maintains statistical accuracy while dramatically improving ease of interpretation and comparison across multiple evaluation items.

Inventive Principle:
Principle #32Color changes

3Illumination intensity

If multiple graphs are created to indicate significance for multiple evaluation items, then the results are visualized, but a large amount of time and effort is required to make such graphs and it imposes a tremendous burden on a reader to examine graphs individually

Engineering Contradiction:
Improvevisual clarityVSAvoidtime to create and examine results
Core Design Contradiction:
Illumination intensityVSLoss of time

Solution Approach 1:

The patent merges multiple individual graphs into a single matrix table that displays all evaluation items simultaneously. Each row represents an evaluation item and each column represents a comparison group, with color-coded cells indicating significance levels. This consolidation eliminates the need to create and examine multiple separate graphs, reducing both the time to generate results and the burden on readers while maintaining visual clarity through color coding.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentUS8775360B2Significance evaluation program and recording medium
Publication Date: 2014.07.08 NAKAMURA MASAO
  • US8775360B2 patent drawing
  • US8775360B2 patent drawing
  • US8775360B2 patent drawing

AI summary

The program makes a computer function as a significance evaluation unit including a statistical equation storage unit which stores algorithms of a plurality of statistical methods, a significance probability calculation unit which calculates significance probability for each of the evaluation items with the algorithm read out from the statistical equation database based on an input signal indicating one statistical method selected, a significance determination unit which determines a magnitude relationship between the significance probability and a significance level which is previously set or input and gives significance information to each of the evaluation items, and an evaluation result output unit which makes a display device output a matrix table in which the same number of cells as that of the evaluation items are provided such that each cell is corresponded to each evaluation item and cells of n columns or n rows are arranged.