In researches statistical tools are of paramount interest since there are some conclusions that can only be arrived into when the data collected is subjected to statistical analysis. In this analysis, the researches are bound to reject or accept hypothesis that were advanced prior to the research. There are quite a number of the statistical techniques. They can be used for some specific interests in a study. One of the possible statistical tools which are frequently used by the researchers is the student’s t-test. The student’s t-test is used to ascertain whether the means of the different samples groups related or not. Within the t-test, there are two sub-divisions which can be found within the test. They are used depending on the treatment that was given to the samples during the study (Samuels, & Witmer, 2003).
In this regard, the t-test may be used differently when the samples are matched or not, this is commonly referred to as an independent t-test. In most cases researchers do make the mistake of using the wrong t-test in analyzing samples. That happens because they do not consider the kind of the treatment that was given to the samples during data collection (Bordens, & Abbott, 2011). Therefore, it is important that this case is to be observed during data analysis in order to avoid giving any deviating results. In the data provided the following can be analyzed by use of the t-test on grounds that they satisfy the component considered when working out the t-test; weight loss after treatment, and Body Mass Index (BMI) before and after the given treatment.
In the t-test for the weight loss after the treatment, the independent t-test will be the most appropriate to be used since the groups will be divided randomly and subsequently they will be given different treatments. Since there is a lack of a clear coherent arrangement of the sample groups considered, the use of the independent t-test comes in handy.
The paired t-test will be considered according to the BMI data that was collected before and after the treatment. In this case, we clearly observe the samples given two treatments, before and after. In this sense, we consider the samples paired on grounds that they are considered vis-a-vis the first data to make a conclusion of the different ways the treatment affects the results (Samuels, & Witmer, 2003). In the case of the paired treatment, the researchers are able to make comparison of the previous results and subsequent results or that the same sample is given two successive treatment over a period of time to observe their effect on the sample so as to enable as draw a conclusion on the two (Bordens, & Abbott, 2011).
The use of the correct version of the t-test in data analysis is of absolute concern since it enables the researchers to avoid missing a significant difference in the data outcome. It is therefore important for one to understand the type of consideration that a data was subjected to as this will enable the analyst to opt for the most appropriate version of the t-test to be used to come up with the most valid results not distorted by the use of a different method in data analysis, otherwise, the results will always have some discrepancies.
References
Bordens, K. S., & Abbott, B. B. (2011). Research design and methods: a process approaches (8th ed.). New York: McGraw-Hill.
Samuels, M. L., & Witmer, J. A. (2003). Statistics for the life sciences (3rd ed.). Upper Saddle River, N.J.: Prentice Hall.