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相关概念视频

Reliability and Validity01:29

Reliability and Validity

13.2K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Prediction Intervals01:03

Prediction Intervals

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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. 
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Surveys02:16

Surveys

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

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A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
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相关实验视频

Updated: Sep 15, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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客观录取数据和州内实践:我们真正能预测什么?

Marlene P Ballejos1, Jamie Riera2, Robert L Williams1

  • 1Department of Family and Community Medicine, University of New Mexico School of Medicine, Albuquerque, NM.

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概括

客观申请人数据在预测医学院毕业生未来实践位置方面具有有限的价值. 招生委员会应优先考虑整体审查,并考虑主观的申请人信息,以解决医疗保健短缺问题.

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科学领域:

  • 医学教育 医学教育
  • 医疗保健服务研究 医疗服务研究
  • 医学院招生录取 医学院招生录取

背景情况:

  • 整体审查在医学院招生中被广泛采用.
  • 预测未来的实践地点仍然是招生委员会面临的挑战.
  • 解决区域医疗保健短缺问题需要了解实践位置预测因素.

研究的目的:

  • 确定客观的申请人属性,预测未来的州内实践地点.
  • 评估客观数据在医学院招生中的有效性,以规划劳动力.

主要方法:

  • 对八个入学队伍 (2006-2013) 的分析.
  • 用于将申请人数据与实践位置联系起来的单变量和多变量回归模型.
  • 客观数据包括人口统计,学术指标 (MCAT,GPA) 和地理信息.

主要成果:

  • 41.7%的毕业生在州内执业.
  • 在州内从业的医生年龄较大,更有可能在医学中代表性较低,来自城市高中,参加了在州内的大学,并获得较低的MCAT分数.
  • 年龄,城市高中出身和MCAT成绩是显著的预测因素 (R2=0.064).

结论:

  • 客观申请人数据对未来的州内实践具有有限的预测价值.
  • 整体审查和主观申请人数据对于预测实践地点至关重要.
  • 需要进一步的研究来确定有价值的主观预测因素.