Name: comparing variance with the f-test
Uploaded: 2024-04-04T10:51:12.000Z
Duration: 1 min 14 s
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Chemistry

CHEM.2

CHEM.2.C

identifying-statistically-significant-differences-the-f-test

Identifying Statistically Significant Differences: The F-Test

F検定は、2つの分散の差が不確定な誤差で説明できないほど大きいかどうかをチェックします。これは、サンプルと母集団の分散、または2つのサンプルの分散を比較します。
F検定は、比較された2つの分散が等しいという帰無仮説に基づいています。
検定統計量Fは分散商として評価され、分散は標準偏差の二乗として表されます。
より大きな値を持つ分散は分子に配置され、F は常に 1 以上になります。
帰無仮説が真であるためには、F 値を 1 にする必要があります。不確定なエラーと確定的なエラーのために 1 より大きくなります。
片側検定では、得られたF値は、選択した信頼水準と自由度で表形式のF値と比較されます。帰無仮説は、得られた F 値が下側片側検定の表形式 F 値より小さい場合、または上部片側検定で大きい場合に棄却されます。

統計的に有意な差異の特定: f 検定

F 検定は、2 つの標本分散を相互に比較したり、標本分散を母集団分散と比較したりするために使用されます。これは、不定誤差が値の違いを説明できるかどうかを判断するために使用されます。 F 検定の使用を可能にする基礎的な仮定には、データデータセットが正規分布に従っていること、およびデータセット内の観測値が互いに独立していることが含まれます。検定統計量 F は、ある分散を別の分散で割ることによって計算されます。言い換えれば、一方の標準偏差の二乗ともう一方の標準偏差の二乗です。商の結果として 1 以上の値を取得するには、常に大きい値を小さい値で割ります。

F 検定の帰無仮説は、比率が 1 に等しいと述べています。検定統計量を計算した後、選択した信頼水準と適切な自由度で、表にまとめられた臨界 F 値と比較されます。検定統計量 F が表にまとめられた臨界 F 値より小さい場合、帰無仮説が受け入れられます。その場合、1 の望ましい値との差異があれば、それは不定の誤差によって正当化され、変動は大きくは変わらないと述べます。

統計的に有意な差異の特定: F 検定

F検定は、2つの分散の差が不確定な誤差で説明できないほど大きいかどうかをチェックします。サンプルの分散と...

Education

JoVE Core

Analytical Chemistry

分析化学

Unit 1

ユニット1

Chemical Applications of Statistical Analyses

統計分析の化学的応用

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

主要用語と概念

comparing variance with the f-test

The F-test compares variance in two data sets or compares a sample variance with a population variance. It helps decide whether an indeterminate error can explain a difference in the values. In statistics, variance shows how spread out the data are.

The test assumes that the data set or sets are normally distributed. It also assumes that the data sets are independent of each other. These conditions must be met before the F-test is used.

The F test statistic is found by dividing one variance by another. That means one standard deviation is squared and divided by the square of the other standard deviation. To get a value of one or greater than one, the larger variance is always divided by the smaller variance.

The null hypothesis for the F-test states that the ratio is equal to 1. After the test statistic is calculated, it is compared with tabulated critical F values at a chosen confidence level and the correct degree of freedom. If the test statistic F is smaller than the tabulated F value, the null hypothesis is rejected. In that case, any difference from unity is explained by indeterminate error, and the variations are not considered significantly different.

Comparing Variance with the F-Test

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identifying statistically significant differences: the f-test

The F-test compares variance in two data sets or compares a sample variance with a population variance. It helps decide whether an indeterminate error can explain a difference in the values. In statistics, variance shows how spread out the data are. The test assumes that the data set or sets are normally distributed. It also assumes that the data sets are independent of each other. These conditions must be met before the F-test is used. The F test statistic is found by dividing one variance...

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key terms and concepts

Learn how the F-test compares variances, checks normality and independence, and uses critical F values to judge whether differences are significant.

Comparing Variance with the F-Test | JoVE K12

JoVE Core 分析化学 は、複雑な化学原理をアニメーションで視覚化することで、SI 単位から NMR 分光法を含むトピックをよりわかりやすくします。実験を撮影した実写動画では、これらの概念が世界中の研究所でどのように応用されているかを取り上げています。

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Comparing Variance with the F-Test

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