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

방법, 표본 또는 분석가 변경이 분석 결과에 미치는 영향은 한 쌍의 실험에서 하나만 변경하여 연구됩니다.
t-검정은 한 평균의 통계적 유의성을 다른 평균의 평균값 또는 알려진 값과 비교합니다.
t-검정에서 쌍을 이루지 않은 데이터는 동일한 소스의 두 개의 독립적인 데이터 집합입니다. 쌍을 이루는 데이터는 두 개의 관련 데이터 집합입니다(예: 일련의 샘플에 대한 두 개의 서로 다른 방법에서 두 개의 집합).
검정 통계량은 알려진 값에 대해 선택한 신뢰 구간에서 파생됩니다. 선택한 유의 수준에서 주어진 자유도에 대한 표로 작성된 검정 통계량 값과 비교하여, 전자의 값이 후자의 범위 내에 있으면 귀무 가설이 허용됩니다.
단측 검정은 증가 또는 감소만 찾는 반면 양측 검정은 어느 방향으로든 변화를 찾습니다.

실험 결과 비교: 학생의 t-검정

t-검정은 표본 평균을 모집단 평균과 비교하거나 두 자료 세트의 두 평균을 비교하는 데 사용되는 통계 방법입니다. 검정 통계량은 선택된 신뢰 구간에서 자료 세트의 표준 편차, 평균 및 측정 횟수로부터 계산된 후 이 신뢰 수준의 임계 값 표와 비교됩니다. 검정 통계량이 임계값보다 작으면 귀무가설이 채택됩니다. 이 경우 평균 간의 차이는 통계적으로 유의하지 않으며 따라서 불확정(무작위) 오류에서 비롯된다고 말합니다. 검정 통계량이 임계값보다 높으면 귀무 가설이 기각됩니다. 이 경우 평균 간의 차이가 통계적으로 유의하며 무작위 오류로 설명할 수 없다고 명시합니다. 차이점은 방법, 샘플링, 분석가 자체의 오류 또는 실제 현상학적 차이에서 비롯됩니다. 통계에서는 페어링된 자료뿐만 아니라 페어링되지 않은 자료에 대해서도 t-검사를 ​​수행할 수 있습니다. 짝을 이루지 않은 자료는 동일한 소스의 두 세트의 반복 측정입니다. 쌍을 이루는 자료는 비교를 위해 두 가지 다른 방법 또는 두 가지 다른 시점에서 동일한 샘플 또는 대상에 대해 수집한 자료를 나타냅니다. t-검정에서 정규분포곡선의 한 쪽 면만 사용하는 경우 단측 검정입니다. t-검정에서 분포의 양쪽을 모두 사용하는 경우 검정은 양측 검정입니다.

실험 결과 비교: 학생의 T-검정

방법, 표본 또는 분석가 변경이 분석 결과에 미치는 영향은 한 쌍의 실험에서 하나만 변경하여 연구됩니다.
그만큼 ...

Education

교육

JoVE Core

Analytical Chemistry

분석 화학

Unit 1

제1단원

Chemical Applications of Statistical Analyses

통계 분석의 화학적 응용

chemical-applications-of-statistical-analyses

KEY TERMS AND CONCEPTS

주요 용어 및 개념

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

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Student's t-Test for Significance Checks

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