One of a two variable relationship is an independent variable while the other variable is dependent (University of the People, n.d.). Dependent samples are paired but occur in one set of items, Meanwhile, independent samples are measured for two different sets of items (How are dependent and independent samples different, n.d.).
In a hypothesis test where two samples are compared, it is important to know which samples are dependent and which are independent. Samples that affect other samples are dependent and are the outcome of interest, while those that do not affect other samples in any way are the independent samples.
For example, in an experiment that tests the outcome of glucose intake on exercise participants—measuring the activity levels of the participants during an exercise before taking the glucose and repeating the measurement…show more content… The concept of comparing two means in both dependent and independent samples involves comparing the two means of two related samples or conditions known as matched or paired samples. In the example above, the pre-test and post-test measurements for the same group of exercise participants before and after taking glucose during the exercise—the paired sample t-test is used to compare the mean difference in the two conditions (before glucose intake and after) to zero. Hence, the null hypothesis assumes that there is no difference in the means of both measurements, while the alternative hypothesis suggests a significant difference and then the t-value is derived by dividing the mean difference by the standard error. Finally, the t-value is compared to the critical value, using the t distribution to check for any statistical
