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

Влияние изменения метода, выборки или аналитика на результаты анализа изучается путем изменения только одного из двух экспериментов.
t-критерий сравнивает статистическую значимость одного среднего со средним значением другого или с известным значением.
В t-критерии непарные данные — это два независимых набора данных из одного и того же источника. Парные данные — это два набора связанных данных, например, два набора из двух разных методов в серии выборок.
Тестовая статистика получается из выбранного доверительного интервала для известного значения. По сравнению с табличным статистическим значением теста для данной степени свободы на выбранном уровне значимости, если первое значение находится в пределах второго, принимается нулевая гипотеза.
Односторонний тест ищет ТОЛЬКО рост или ТОЛЬКО снижение, в то время как двухсторонний тест ищет изменение в любом направлении.

Сравнение экспериментальных результатов: Т-критерий Студента

T-критерий — это статистический метод, используемый для сравнения среднего значения выборки со средним значением генеральной совокупности или сравнения двух средних значений из двух наборов данных. Статистика теста рассчитывается на основе стандартного отклонения, среднего значения и количества измерений в наборе данных на выбранном доверительном интервале, а затем сравнивается с таблицей критических значений на этом уровне достоверности. Если статистика теста меньше критического значения, принимается нулевая гипотеза. В этом случае мы утверждаем, что разница между средними значениями не является статистически значимой и, следовательно, возникает из-за неопределенных (случайных) ошибок. Если статистика теста выше критического значения, нулевая гипотеза отклоняется. В этом случае мы констатируем, что разница между средними статистически значима и не может быть объяснена случайными ошибками. Разница возникает из-за ошибок в методе, выборке, самих аналитиков или из-за истинных феноменологических различий. В статистике t-тесты можно проводить как на парных, так и на непарных данных. Непарные данные представляют собой два набора повторных измерений из одного и того же источника; парные данные относятся к данным, полученным для одних и тех же образцов или субъектов двумя разными методами или в два разных момента времени для сравнения. Когда в t-тесте используется только одна сторона кривой нормального распределения, это односторонний тест. Если в t-тесте используются обе стороны распределения, тест является двусторонним

Влияние изменения метода, выборки или аналитика на результаты анализа изучается путем изменения только одного из двух экспериментов.
Тем...

Education

JoVE Core

Analytical Chemistry

Аналитическая химия

Unit 1

Раздел 1

Chemical Applications of Statistical Analyses

Применение статистического анализа в химии

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

ОСНОВНЫЕ ТЕРМИНЫ И ПОНЯТИЯ

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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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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