T-tests in Quantitative Doctoral Business Research
Quantitative research is one of the methodologies that is commonly used in doctoral business research. The use of this approach is attributable to the availability of more data that requires analysis to help generate competitive advantage in the business field. The use of quantitative research entails conducting statistical analysis, which involves the use of different methods such as t-tests and ANOVA. T-test is used in hypothesis testing in quantitative studies to determine whether variations between the averages of two groups is unlikely to have emerged because of a random chance in selection of a sample. In essence, t-tests help to compare whether two groups have varying average values. In light of the role and significance of the assumptions underlying each parametric test, this paper provides a comparison of one-sample, paired-samples, and independent-sample t-tests within the context of quantitative doctoral business research. The comparison is based on a qualitative research proposal.
One-sample, Paired-Samples, and Independent-Samples T-tests
As previously indicated, t-tests are used in quantitative research evaluate whether two groups have varying average values. In this regard, t-tests help to compare two means to evaluate whether they come from the same population. One of the underlying assumptions in t-tests is that both groups have relatively equal variances and are normally distributed. However, when a two-sample t-test is conducted, it is presumed that two groups have relatively equal variances, while the other does not (Lumley et al., 2002).
One-sample t-test is used to compare the average value of one group to a single number or to...
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