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

La influencia de cambiar el método, la muestra o el analista en los resultados del análisis se estudia alterando solo uno de un par de experimentos.
La prueba t compara la significación estadística de una media con el valor medio de otra o con un valor conocido.
En una prueba t, los datos no emparejados son dos conjuntos independientes de datos de la misma fuente. Los datos emparejados son dos conjuntos de datos relacionados, por ejemplo, dos conjuntos de dos métodos diferentes en una serie de muestras.
El estadístico de prueba se deriva del intervalo de confianza seleccionado para un valor conocido. En comparación con el valor estadístico de prueba tabulado para un grado de libertad dado en un nivel de significación elegido, si el primer valor está dentro del rango del segundo, se acepta la hipótesis nula.
Una prueba de una cola busca SOLO un aumento o SOLO una disminución, mientras que una prueba de dos colas busca un cambio en cualquier dirección.

comparación de resultados experimentales: prueba t de student

La prueba t es un método estadístico que se utiliza para comparar la media de la muestra con una media de la población o comparar dos medias de dos conjuntos de datos. La estadística de prueba se calcula a partir de la desviación estándar, la media y el número de mediciones en el conjunto de datos en un intervalo de confianza seleccionado y luego se compara con una tabla de valores críticos en este nivel de confianza. Si el estadístico de prueba es menor que el valor crítico, se acepta la hipótesis nula. En este caso afirmamos que la diferencia entre las medias no es estadísticamente significativa y por tanto proviene de errores indeterminados (aleatorios). Si el estadístico de prueba es mayor que el valor crítico, se rechaza la hipótesis nula. En este caso, afirmamos que la diferencia entre las medias es estadísticamente significativa y no puede explicarse por errores aleatorios. La diferencia proviene de errores en el método, en el muestreo, en los propios analistas o en verdaderas diferencias fenomenológicas. En estadística, las pruebas t se pueden realizar con datos emparejados y no emparejados. Los datos no apareados son dos conjuntos de mediciones replicadas de la misma fuente; Los datos pareados se refieren a datos tomados de las mismas muestras o sujetos de dos métodos diferentes o en dos momentos diferentes para comparar. Cuando en la prueba t se utiliza solo un lado de una curva de distribución normal, se trata de una prueba de una cola. Si se utilizan ambos lados de la distribución en la prueba t, la prueba es de dos colas.

Comparación de resultados experimentales: Prueba T de Student

La influencia de cambiar el método, la muestra o el analista en los resultados del análisis se estudia alterando solo uno de un par de experimentos.
El...

Education

Educación

JoVE Core

Analytical Chemistry

Química Analítica

Unit 1

Unidad 1

Chemical Applications of Statistical Analyses

Aplicaciones Químicas de los Análisis Estadísticos

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

TÉRMINOS Y CONCEPTOS CLAVE

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

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

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Student's t-Test for Significance Checks

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