Selecting an appropriate statistical method is an important step in analyzing research data. Selecting the wrong statistical analysis method creates serious challenges when interpreting a study’s findings and affects the conclusions drawn from the studies (Mishra et al., 2019). In statistics, for each specific situation, there are appropriate statistical methods available for analyzing and interpreting data. Mishra et al. (2019) explain that selecting the appropriate statistical method requires knowledge concerning the assumptions and conditions of statistical methods, the nature and type of the data collected, and study objectives since appropriate statistical methods are selected based on these factors. This paper contributes to an enhanced understanding of statistical analysis methods by proposing five hypothetical research studies for five statistical analysis approaches. The statistical analysis methods include independent samples t-test, paired samples t-test, correlation, regression, and chi-square test.

Independent Samples T-Test

An important point to consider when selecting a statistical test is to assess whether the data is paired. According to Mishra et al. (2019), an independent samples t-test is used when different groups are used in a study, and each group has different subjects. For instance, comparing the means between two groups with unpaired or independent data. An independent samples t-test is used to compare two sample means from unrelated groups. Below is a hypothetical study that applies independent samples t-test.

The Hypothetical Study

A proposed hypothetical study analyses the salary differences between male and female employees within a large organization following complaints of gender pay gaps that must be addressed for fairness to prevail.

Main Variables in the Study

In the study that analyzes the salary differences between male and female employees, the independent variable is gender (male/female), and the dependent variable is employees’ salaries.

The Nature of the Data That Will Be Collected

Salary data is the first data that will be collected for the study. Salary data will be obtained for all the employees, including their gender. Data on the control variables that could influence salaries will also be collected, including job titles, years of experience, and education levels. Demographic data, including age, department, and tenure, would also be collected. Collecting employee performance data would also be important, which could help explain salary differences.

Research Question

Is there a statistically significant difference in the organization’s average salaries between female and male employees?

The Test Used

An independent samples t-test will be used. Mishra et al. (2019) say that the test is appropriate when comparing the means of two independent groups. In this case, the independent groups are male and female employees. The test will help determine whether any observed differences in average salaries are statistically significant or occur randomly based on other factors. In the t-test, the t-statistic will measure the differences between the means of the male and female groups, and the p-value will indicate whether the difference is statistically significant. A p-value of less than 0.05 would suggest a significant difference in the salaries between male and female employees.

Paired Samples T-Test

When considering whether data is paired, the independent samples t-test is not the only applicable test for unpaired data. When data is paired, such as when the same subjects are measured at different points or using different methods, a paired samples t-test is used. A paired samples t-test compares the means between two groups with paired data (Mishra et al., 2019). An example of a hypothetical research study is described below for paired samples t-test.

The Hypothetical Study

A hypothetical study that uses paired samples t-test aims to find the differences in self-esteem levels in a specific group of individuals before and after they are subjected to a self-esteem improvement program.

Main Variables in the Study

The study’s independent variable will be the intervention applied in the study. The self-esteem intervention used in the program is the independent variable since it will be manipulated or introduced to assess its impact on self-esteem levels. This means that the self-esteem levels are the dependent variable.

The Nature of the Data That Will Be Collected

Data will be collected before and after the self-esteem intervention. The data will be self-esteem