一种新的方法,用于近似的p值的一类双变的标志测试测试
Ibrahim A A Shanan1,2, Ehab F Abd-Elfattah1, Abd El-Raheem M Abd El-Raheem3
1Department of Mathematics, Faculty of Education, Ain Shams University, Cairo, Egypt.
Scientific reports
|November 5, 2023
概括
本研究介绍了非参数双变量测试的点近似方法,为计算各种科学领域的确切p值提供了比正常近似方法更好的替代方案.
科学领域:
- 统计 统计 统计 统计
- 应用数学 应用数学 应用数学
- 数据分析 数据分析
背景情况:
- 在各种科学和经济领域,双变量数据分析至关重要.
- 与参数方法相比,非参数方法提供了灵活性.
- 准确的p值计算对于在双变量分析中测试假设至关重要.
研究的目的:
- 提出坐点近似作为在非参数双变量测试中近似精确p值的方法.
- 为了比较角近似与传统的非对称正常近似的有效性.
- 在双变量统计分析中为p值估计提供更准确的替代方案.
主要方法:
- 使用了坐点近似方法,利用产生动量功能的方法.
- 应用该方法来近似准确的p值非参数双变量试验.
- 使用蒙特卡洛模拟和现实世界双变量数据集进行了比较分析.
主要成果:
- 坐点近似方法表现出优异的性能,与非对称的正常近似方法相比.
- 模拟研究表明,p值近似度的准确性有所提高.
- 对真实数据示例的分析支持了该方法的有效性.
结论:
- 坐点近似是非参数双变量测试中p值计算的可行和更准确的替代方案.
- 这种方法提高了对双变量数据的统计推断的可靠性.
- 这些发现表明,在使用复杂的双变量数据分析的领域,应用范围更广.
相关概念视频
Sign Test for Matched Pairs
137
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
137
Introduction to the Sign Test
848
The sign test is an important tool in nonparametric statistics, offering a straightforward yet effective method for analyzing matched pairs, nominal data, or hypotheses concerning the median of a population. It transforms data points into positive or negative signs, avoiding the need for assumptions about data distribution and instead focusing on the direction of change. It is particularly valuable when data does not conform to the normal distribution requirements of many parametric tests. For...
848
Sign Test for Nominal Data
101
The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
For example, consider a...
101
Decision Making: P-value Method
5.4K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.4K
Sign Test for Median of Single Population
118
In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
118
Bonferroni Test
2.7K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.7K


