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Prediction Intervals01:03

Prediction Intervals

3.5K
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. 
3.5K
Improving Translational Accuracy02:07

Improving Translational Accuracy

15.3K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
15.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

3.7K
3.7K
Margin of Error01:27

Margin of Error

7.9K
The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.
7.9K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

11.2K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
11.2K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.3K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.3K

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関連する実験動画

国際的な選挙予測の改善

Ryan Kennedy1, Stefan Wojcik2,3, David Lazer2,3

  • 1Center for International and Comparative Studies, University of Houston, Houston, TX, USA. rkennedy@uh.edu.

Science (New York, N.Y.)
|February 4, 2017
PubMed
まとめ
この要約は機械生成です。

世界的な選挙予測モデルは 80~90%の確率で結果を正確に予測します 政治機関,現役優位性,国際的要因が 選挙結果に大きく影響し,世論調査のデータは 強力な予測要因であることが証明されています.

関連する実験動画

科学分野:

  • 政治科学
  • コンピュータ社会科学
  • 国際関係

背景:

  • 選挙の結果を予測することは 民主的なプロセスを理解するために 極めて重要です
  • 過去のモデルには グローバルな範囲や包括的なデータが 欠けていました
  • 直接的な行政選挙に様々な要因が及ぼす影響については,さらなる調査が必要である.

研究 の 目的:

  • 直接選挙を予測するためのモデルを開発し,検証する.
  • 各国の選挙結果を予測する 重要な要因を特定する
  • 選挙予測における投票データの役割を評価する.

主な方法:

  • 86カ国の500以上の選挙のデータセットを使用しました.
  • 146回の選挙から集めた 広範なデータセットを使用した.
  • 試料外テストとリアルタイム予測実験で検証されたモデル.

主要な成果:

  • モデルが80~90%の精度で 選挙結果を予測しました
  • 政治機関,既存の優位性,国際的つながり/援助が重要な予測要因でした.
  • 経済指標の予測力は比較的弱かった.
  • 世界の世論調査のデータでは 発展途上国でも 予測の強さが見られました

結論:

  • 世界的な選挙は成功裏にモデル化され 予測可能になっています
  • 政治機関と現役の優位性は 選挙結果を大きく左右します
  • 国際的要因と世論調査データは 選挙の正確な予測に不可欠です