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相关概念视频

Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K
Interval Level of Measurement00:55

Interval Level of Measurement

14.5K
For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
14.5K
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

1.5K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
1.5K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

105
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
105
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.3K
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...
5.3K
Experimental Designs01:16

Experimental Designs

11.2K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
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相关实验视频

Updated: Jun 16, 2025

Interactive and Visualized Online Experimentation System for Engineering Education and Research
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Interactive and Visualized Online Experimentation System for Engineering Education and Research

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基于区间值模糊集合的虚拟实验教学评估模型的研究.

Qi Cao1, Wei Zhong1

  • 1Army Logistics University, Chongqing, China.

Evaluation and program planning
|May 3, 2025
PubMed
概括

本研究引入了一个新的间隔值模糊综合评估 (IVFCE) 模型,用于虚拟实验教学 (VET). 通过IVFCE模型,可以更有说服力,更详细地评估职业教育和培训的质量,帮助不断改进.

科学领域:

  • 教育技术的教育技术
  • 模糊的数学 模糊的数学
  • 数据分析 数据分析

背景情况:

  • 虚拟实验教学 (VET) 的评估是复杂的,涉及多个指标和固有的不确定性.
  • 传统的模糊评估方法在处理间隔值时可能会丢失信息.
  • 准确的职业教育评估对于提高教学质量至关重要.

研究的目的:

  • 提出一个以间隔值为基础的模糊综合评估 (IVFCE) 模型,用于VET.
  • 为应对职业教育评估中不确定性和信息丢失所带来的挑战.
  • 为虚拟实验提供一个更强大,更有信息性的评估框架.

主要方法:

  • 使用区间值模糊集 (IVFS) 理论来处理区间数据.
  • 开发一个职业教育和培训的多层次综合评估模型.
  • 将IVFCE结果与传统的模糊综合评估方法进行比较.

主要成果:

  • 拟议的IVFCE模型提供了更有说服力的评估结果.
  • 与传统方法相比,该模型有效减少了信息丢失.
  • 通过IVFCE,人们可以更好地了解职业教育标准和需要改进的领域.
关键词:
评估模型的评估模型.区间估值的模糊综合性评估.教学评估的教学评价.虚拟实验教学是一种虚拟的实验教学.

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A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

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结论:

  • 通过IVFCE模型,提高了职业教育评估的准确性和全面性.
  • 这种方法更好地反映了虚拟实验教学的复杂性和多样性.
  • 该模型支持在虚拟实验教学中不断提高质量.