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相关概念视频

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

22.7K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
22.7K
Ranks01:02

Ranks

211
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
211
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

125
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
125
Kendall's Tau Test01:16

Kendall's Tau Test

555
Kendall's tau test, also known as the Kendall rank coefficient test, is a nonparametric method for assessing association between two variables. This test is particularly useful for identifying significant correlations when the distributions of the sample and population are unknown. Developed in 1938 by the British statistician Sir Maurice George Kendall, the tau coefficient (denoted as τ) serves as a rank correlation coefficient, with values ranging from -1 to +1.
A τ value...
555
Scatter Plot01:15

Scatter Plot

6.7K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
6.7K
One-Way ANOVA01:18

One-Way ANOVA

7.6K
One-way ANOVA analyzes more than three samples categorized by one factor. For example, it can compare the average mileage of sports bikes. Here, the data is categorized by one factor - the company. However, one-way ANOVA cannot be used to simultaneously compare the sample mean of three or more samples categorized by two factors. An example of two factors would be sports bikes from different companies driven in different terrains, such as a desert or snowy landscape. Here, two-way ANOVA is used...
7.6K

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相关实验视频

Updated: May 20, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

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艺术绘画中的二乘二顺序图案.

Mateus M Tarozo1, Arthur A B Pessa1, Luciano Zunino2,3

  • 1Departamento de Física, Universidade Estadual de Maringá, Maringá, PR 87020-900, Brazil.

PNAS nexus
|March 27, 2025
PubMed
概括

研究人员分析了14万幅画中的像素强度的排序模式. 简单的,普遍适用的图案揭示了对艺术风格及其1000年来演变的洞察力.

关键词:
艺术史 艺术史 艺术史复杂性的复杂性 复杂性的复杂性审美措施 审美措施空间模式 空间模式

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Generating Strictly Controlled Stimuli for Figure Recognition Experiments

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Investigating the 'Uncatchable Smile' in Leonardo da Vinci's La Bella Principessa: A Comparison with the Mona Lisa and Pollaiuolo's Portrait of a Girl
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Investigating the 'Uncatchable Smile' in Leonardo da Vinci's La Bella Principessa: A Comparison with the Mona Lisa and Pollaiuolo's Portrait of a Girl

Published on: October 4, 2016

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相关实验视频

Last Updated: May 20, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Generating Strictly Controlled Stimuli for Figure Recognition Experiments

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Investigating the 'Uncatchable Smile' in Leonardo da Vinci's La Bella Principessa: A Comparison with the Mona Lisa and Pollaiuolo's Portrait of a Girl
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科学领域:

  • 计算式的艺术史研究
  • 数字人文学科 数字人文学科
  • 图像分析 图像分析

背景情况:

  • 视觉艺术的定量分析正在随着数字化收藏而扩大.
  • 了解空间结构是关键,但定义简单的,普遍的单位是具有挑战性的.
  • 以前的研究往往缺乏用于艺术分析的普遍适用的指标.

研究的目的:

  • 为分析绘画和艺术风格开发普遍适用的,可解释的单位.
  • 在一个大,多样化的艺术数据集中调查像素强度的排序模式.
  • 建立一个标准化度量来比较艺术品和跟踪风格演变.

主要方法:

  • 从约14万幅数字化绘画中分析了2x2像素强度分区中的排序模式.
  • 基于连续性和对称性的模式被分为11种类型.
  • 统计分析不同艺术群体和不同时期的模式分布和流行情况.

主要成果:

  • 确定了11种适用于任何风格或时代的绘画的普遍排序模式类型.
  • 发现了这些模式的普遍分布,通过像素强度关系调制.
  • 证明这些图案与低级别的视觉特征相关,并可以识别绘画风格.
  • 随着时间的推移,观察到与平均模式流行率相差越来越大的趋势,特别是在20世纪30年代之后.

结论:

  • 像素强度中的普通模式为艺术分析提供了标准化的定量度量.
  • 这些模式提供了对艺术风格特征及其历史演变的洞察.
  • 随着时间的推移,艺术作品呈现出越来越多的风格分歧,具有显著的变化和不均的进化.