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

Wpływ zmiany metody, próbki lub analityka na wyniki analizy jest badany poprzez zmianę tylko jednego z dwóch eksperymentów.
Test t porównuje istotność statystyczną jednej średniej ze średnią innej lub ze znaną wartością.
W teście t niesparowane dane to dwa niezależne zestawy danych z tego samego źródła. Dane sparowane to dwa zestawy powiązanych ze sobą danych, na przykład dwa zestawy z dwóch różnych metod na serii próbek.
Statystyka testowa jest uzyskiwana na podstawie wybranego przedziału ufności dla znanej wartości. W porównaniu z tabelaryzowaną wartością statystyczną testu dla danego stopnia swobody na wybranym poziomie istotności, jeżeli pierwsza wartość mieści się w zakresie drugiej, przyjmuje się hipotezę zerową.
Test jednostronny szuka TYLKO wzrostu lub TYLKO spadku, podczas gdy test dwustronny szuka zmiany w dowolnym kierunku.

porównywanie wyników eksperymentów: test t-studenta

Test t jest metodą statystyczną stosowaną do porównania średniej próbki ze średnią populacji lub porównania dwóch średnich z dwóch zbiorów danych. Statystykę testową oblicza się z odchylenia standardowego, średniej i liczby pomiarów w zestawie danych w wybranym przedziale ufności, a następnie porównuje z tabelą wartości krytycznych na tym poziomie ufności. Jeżeli statystyka testowa jest mniejsza od wartości krytycznej, przyjmuje się hipotezę zerową. W tym przypadku stwierdzamy, że różnica między średnimi nie jest istotna statystycznie i dlatego wynika z błędów nieokreślonych (losowych). Jeżeli statystyka testowa jest wyższa od wartości krytycznej, hipoteza zerowa zostaje odrzucona. W tym przypadku stwierdzamy, że różnica pomiędzy średnimi jest istotna statystycznie i nie można jej wytłumaczyć błędami przypadkowymi. Różnica wynika z błędów metody, próbkowania, samych analityków lub prawdziwych różnic fenomenologicznych. W statystyce testy t można przeprowadzić zarówno na danych niesparowanych, jak i sparowanych. Dane niesparowane to dwa zestawy powtórzonych pomiarów z tego samego źródła; dane sparowane odnoszą się do danych pobranych na tych samych próbkach lub osobach dwiema różnymi metodami lub w dwóch różnych punktach czasowych w celach porównawczych. Jeżeli w teście t używana jest tylko jedna strona krzywej rozkładu normalnego, jest to test jednostronny. Jeżeli w teście t zostaną użyte obie strony rozkładu, test będzie dwustronny.

Porównywanie wyników eksperymentów: Test T-Studenta

Wpływ zmiany metody, próbki lub analityka na wyniki analizy jest badany poprzez zmianę tylko jednego z dwóch eksperymentów.
Ten...

Education

JoVE Core

Analytical Chemistry

Chemia analityczna

Unit 1

Jednostka 1

Chemical Applications of Statistical Analyses

Zastosowania analiz statystycznych w chemii

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

KLUCZOWE TERMINY I POJĘCIA

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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