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相关概念视频

z Scores and Area Under the Curve01:17

z Scores and Area Under the Curve

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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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Normal Distribution01:11

Normal Distribution

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The normal, a continuous distribution, is the most important of all the distributions. Its graph is a bell-shaped symmetrical curve, which is observed in almost all disciplines. Some of these include psychology, business, economics, the sciences, nursing, and, of course, mathematics. Some instructors may use the normal distribution to help determine students’ grades. Most IQ scores are normally distributed. Often real-estate prices fit a normal distribution. The normal distribution is...
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Central Limit Theorem01:14

Central Limit Theorem

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The central limit theorem, abbreviated as clt, is one of the most powerful and useful ideas in all of statistics. The central limit theorem for sample means says that if you repeatedly draw samples of a given size and calculate their means, and create a histogram of those means, then the resulting histogram will tend to have an approximate normal bell shape. In other words, as sample sizes increase, the distribution of means follows the normal distribution more closely.
The sample size, n, that...
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Introduction to z Scores01:05

Introduction to z Scores

343
A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

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A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
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Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
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相关实验视频

Updated: Jun 5, 2025

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
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为波兰人口定制的出生体重标准.

Anna Kajdy1, Oliver Hugh2, Jan Modzelewski1

  • 1Centre of Postgraduate Medical Education, Department of Reproductive Health, Warsaw, Poland.

Archives of medical science : AMS
|December 9, 2024
PubMed
概括

与芬顿标准相比,波兰定制的出生体重图表提高了胎儿生长限制 (FGR) 的检测,并识别了更多的风险新生儿. 这种个性化的方法提高了新生儿不良结果的识别.

关键词:
出生时的体重出生时的体重.提供定制的系数.与妊娠相关的最佳体重与妊娠相关的最佳体重新生儿结局 新生儿结局对于妊娠年龄来说小.

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科学领域:

  • 产科和妇科 产科和妇科
  • 新生儿健康 新生儿健康
  • 生物统计学 生物统计学

背景情况:

  • 定制的生长图表有助于检测胎儿生长限制 (FGR) 和减少假阳性.
  • 制定特定人口的标准对于准确的胎儿生长评估至关重要.

研究的目的:

  • 为波兰人口创建一个定制的出生体重标准.
  • 为了比较定制标准与芬顿标准在识别有风险的新生儿方面的有效性.

主要方法:

  • 分析了4270例怀孕的数据.
  • 收集了母亲和新生儿的变量,包括身高,体重,种族,妊娠年龄和并发症.
  • 后向渐进式多重回归被用来推导定制标准的系数.

主要成果:

  • 定制标准发现妊娠年龄 (SGA) 小小的比率更高,为11.9%,而芬顿标准为6.6%.
  • 定制标准确定了显著更多的新生儿存在死产,新生儿重症监护室入院和其他并发症的风险.
  • 量化了影响出生体重的生理和病理因素,包括母亲的年龄和高血压.

结论:

  • 定制的出生体重标准优于芬顿标准,用于识别波兰人口中SGA新生儿的不良结果.
  • 这种定制方法提高了危险怀孕的检测,并改善了新生儿护理计划.