Name: student's t-test for significance checks
Uploaded: 2024-04-04T10:51:12.000Z
Duration: 1 min 9 s
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Chemistry

CHEM.2

CHEM.2.C

comparing-experimental-results-student-s-t-test

Comparing Experimental Results: Student's t-Test

A influência da mudança do método, da amostra ou do analista nos resultados da análise é estudada alterando apenas um em um par de experimentos.
O teste t compara a significância estatística de uma média com o valor médio de outra ou com um valor conhecido.
Em um teste t, os dados não pareados são dois conjuntos independentes de dados da mesma fonte. Os dados emparelhados são dois conjuntos de dados relacionados, por exemplo, dois conjuntos de dois métodos diferentes em uma série de amostras.
A estatística de teste é derivada do intervalo de confiança selecionado para um valor conhecido. Em comparação com o valor estatístico do teste tabulado para um determinado grau de liberdade em um nível de significância escolhido, se o primeiro valor estiver dentro do intervalo do último, a hipótese nula é aceita.
Um teste unicaudal procura APENAS um aumento ou APENAS uma diminuição, enquanto um teste bicaudal procura uma mudança em qualquer direção.

comparando resultados experimentais: teste t de estudante

O teste t é um método estatístico usado para comparar a média da amostra com a média da população ou comparar duas médias de dois conjuntos de dados. O valor de teste é calculado a partir do desvio padrão, da média e do número de medições no conjunto de dados em um intervalo de confiança selecionado e depois comparado a uma tabela de valores críticos nesse nível de confiança. Se o valor de teste for menor que o valor crítico, a hipótese nula é aceita. Nesse caso, afirmamos que a diferença entre as médias não é estatisticamente significativa e, portanto, provém de erros indeterminados (aleatórios). Se o valor de teste for superior ao valor crítico, a hipótese nula é rejeitada. Nesse caso, afirmamos que a diferença entre as médias é estatisticamente significativa e não pode ser explicada por erros aleatórios. A diferença vem de erros no método, na amostragem, nos próprios analistas ou em verdadeiras diferenças fenomenológicas. Em estatística, os testes t podem ser realizados tanto em dados não pareados quanto em dados pareados. Dados não pareados é dois conjuntos de medições replicadas da mesma fonte; dados pareados referem-se a dados obtidos nas mesmas amostras ou sujeitos a partir de dois métodos diferentes ou em dois momentos diferentes para comparação. Quando apenas um lado de uma curva de distribuição normal é usado no teste t, trata-se de um teste unicaudal. Se ambos os lados da distribuição forem usados ​​no teste t, o teste será bicaudal.

Comparando Resultados Experimentais: Teste T de Estudante

A influência da mudança do método, da amostra ou do analista nos resultados da análise é estudada alterando apenas um em um par de experimentos.
O...

Education

JoVE Core

Analytical Chemistry

Química Analítica

Unit 1

Unidade 1

Chemical Applications of Statistical Analyses

Aplicações Químicas de Análises Estatísticas

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

TERMOS E CONCEITOS-CHAVE

student's t-test for significance checks

Student's t-test is a statistical tool for checking whether two means are different in a meaningful way. It can compare a sample mean with a population mean, or it can compare the means from two data sets. The test uses the mean, standard deviation, and number of measurements, along with a chosen confidence interval.

The test statistic is then compared with a table of critical values at that confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. That means the difference between the means is not statistically significant and is likely due to random, indeterminate errors.

If the test statistic is higher than the critical value, the null hypothesis is rejected. In that case, the difference is statistically significant and cannot be explained by random errors alone. The cause may come from the method, the sampling, the analyst, or a real difference in the phenomenon being studied.

Student's t-tests can be used with unpaired or paired data. Unpaired data are two sets of replicate measurements from the same source. Paired data are measurements taken on the same samples or subjects with two methods, or at two different time points, for comparison. The test can also be one-tailed, when only one side of the normal distribution curve is used, or two-tailed, when both sides are used.

Student's t-Test for Significance Checks

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comparing experimental results: student's t-test

Student's t-test is a statistical tool for checking whether two means are different in a meaningful way. It can compare a sample mean with a population mean, or it can compare the means from two data sets. The test uses the mean, standard deviation, and number of measurements, along with a chosen confidence interval. The test statistic is then compared with a table of critical values at that confidence level. If the test statistic is smaller than the critical value, the null hypothesis is...

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key terms and concepts

Learn how Student's t-test compares means, uses critical values, and helps decide whether a result is statistically significant in high school science.

Student's t-Test for Significance Checks | JoVE K12

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Student's t-Test for Significance Checks

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