相关实验视频

Updated: Jul 28, 2025

Methods to Evaluate Cytotoxicity and Immunosuppression of Combustible Tobacco Product Preparations
09:25

Methods to Evaluate Cytotoxicity and Immunosuppression of Combustible Tobacco Product Preparations

Published on: January 10, 2015

11.5K

只有小于0.05的p值是有意义的吗? 一个大于0.05的值也很重要!

Sanggyu Kwak1

  • 1Department of Medical Statistics, Daegu Catholic University School of Medicine, Daegu, Korea.

Journal of lipid and atherosclerosis
|June 2, 2023
PubMed
概括

统计假设测试需要精确的结论,超越"显著或不显著"到"统计显著或不统计显著". 研究人员必须仔细设定显著性水平,因为它会影响研究结果.

关键词:
统计数据分析 统计数据分析统计数据的解释统计 统计 统计 统计

更多相关视频

Author Spotlight: Advancing Caenorhabditis elegans Research Using Paraformaldehyde-Treated Bacteria06:58

Author Spotlight: Advancing Caenorhabditis elegans Research Using Paraformaldehyde-Treated Bacteria

Published on: July 28, 2023

2.4K
Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

18.5K

相关概念视频

P-value01:10

P-value

P-value is one of the most crucial concepts in statistics.
P-value stands for the probability value.  P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to  not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...
7.0K
Statistical Significance01:50

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
20.2K
Decision Making: P-value Method01:09

Decision Making: P-value Method

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...
5.5K
Significance Testing: Overview01:04

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
3.4K
Critical Region, Critical Values and Significance Level01:16

Critical Region, Critical Values and Significance Level

The critical region, critical value, and significance level are interdependent concepts crucial in hypothesis testing.
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in  probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
12.0K
Bonferroni Test01:10

Bonferroni Test

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...
2.8K