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Correlation and causation- paired t tes
A paired t-test is used when we need to conduct a hypothesis comparing means of a normal distribution which has a dependent variable measured as a continuous ratio level or interval, and an independent variable which consists of two related groups.
When researchers analyze the cholesterol level of a group of individuals before and after taking a new low-fat diet for 16 weeks to lower their cholesterol, the researchers indicate that a low-fat diet for 16 weeks will reduce the cholesterol level of people, and prove that researchers want to conduct a hypothesis of paired t-test. That is an example and clearly, it is a paired t-test where the dependent variable is the cholesterol level, a continuous ratio level variable, and the independent variable is a discrete categorical variable of two related groups which are the before and after takes the low-fat diet.
In conclusion, a paired t-test is that which is considered a parametric statistics because its dependent variable is continuous and normally distributed and the independent variable is one (no explicit) categorical variable conformed by two related groups.
What do the results mean in this study? What about the p-value? What research bias may have come into play here? Is there a way to control for it?
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2012). Statistical techniques in business and economics. New York, NY: McGraw-Hill/Irwin.
Trochim, W. (2006). The t-test. Research Methods Knowledge Base. Retrieved