Online Article

Introduction to t-test statistics

2nd February 2023

Related topic: Quantitative research

Author: Ady Hameme N. A.

T-test statistics are a statistical tool used to determine if there is a significant difference between two groups or samples. This test is commonly used in fields such as psychology, education, and biology to compare means of two groups or samples and determine if the difference between them is statistically significant.

Cohen (1988) introduced the concept of "effect size," which is a measure of the magnitude of the difference between two groups. This is an important consideration when conducting a t-test, as it allows researchers to determine the practical significance of the results, in addition to the statistical significance.

Snedecor and Cochran (1989) outlined the steps for conducting a t-test, including selecting the appropriate sample size, selecting the appropriate test statistic, and calculating the p-value. The p-value is a measure of the likelihood that the results were obtained by chance, and a p-value of less than 0.05 is considered statistically significant.

Stevens (1992) emphasized the importance of understanding the assumptions underlying the t-test, including the assumption of normality and the assumption of equal variances between the two groups. Violating these assumptions can affect the validity of the results.

Field (2013) discussed the use of t-tests in the context of analyzing data from experiments, including the use of paired t-tests to compare the means of two related groups. He also discussed the use of one-sample t-tests to compare the mean of a sample to a known population mean.

Gravetter and Wallnau (2017) emphasized the importance of understanding the limitations of t-tests, including the assumption of independence between the two groups being compared. They also discussed the use of alternative tests, such as nonparametric tests, when the assumptions of the t-test are not met.

Levine and Markus (2014) discussed the use of t-tests in the context of comparing means between groups in social psychology research. They emphasized the importance of conducting a power analysis to determine the appropriate sample size and the importance of using multiple statistical tests to confirm the results.

Overall, t-test statistics are a useful tool for comparing means between two groups or samples and determining if the difference between them is statistically significant. However, it is important to understand the assumptions and limitations of the t-test and to consider alternative tests when necessary.

Cite this article: Ady Hameme, N. A. (2023, February 2). Introduction to t-test statistics. Retrieved <insert month> <insert date>, <insert year>, from https://www.myadvrc.com/publications/article-13

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