Descriptive research design helps in gathering information that will display relationships between variables without changing the environment (U.S Department of Health and Human Services: The Office of Research Integrity, n.d.). The use of independent sample t-test is an appropriate choice for a study of t-test method that compares means of two groups of cases. When you are creating hypothesis tests, the t test permits you to appraise approximations from samples to select if modifications occur between these groups in the sample. The p-value, which stands for probability value, is an important value to consider when calculating statistical significant. It is the likelihood of spotting t-value of equal or greater entire value beneath the null hypothesis. If your p-value connected with your t-test is small or often 0.05, there is resilient that the mean is not the same from the alternative hypothesis (Wagner, 2016). You can alternatively use confidence level to identify the 95% confidence interval of your difference. These are the lower and upper bound of the confidence interval for the mean difference. It is significant to note how confidence interval is said to be the range of values showing lower and upper bound, in which, for example, there is blank % likelihood that the hours spent on science homework/studying in typical school week is between upper and lower bound. It is a boundary of stated values that tend to show likelihood in which value of constraint lies with it (Wagner, 2016). In order for a null hypothesis to be rejected it has to be tested to show that there is no difference that can contradict the research hypothesis (Frankfort-Nachmias & Leon-Guerrero, 2015). You could decide to use equal variances as not assumed to reject null hypothesis when P-value is set to 0.05 or lower.
Reference:
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society
(7th ed.). Thousand Oaks, CA: Sage Publications.
U.S Department of Health and Human Services: The Office of Research Integrity. (n.d.). Descriptive Studies. Retrieved from http://ori.hhs.gov/education/products/sdsu/res_des1.htm
Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications.
