All t tests are used as standalone analyses for very simple experiments and research questions as well as to perform individual tests within more complicated statistical models such as linear regression. The characteristics of the data dictate the appropriate type of t test to run. The t test is especially useful when you have a small number of sample observations (under 30 or so), and you want to make conclusions about the larger population. ![]() Since each of the plants is used in both soil types, she can use a paired samples t-test to determine if the mean evaporation is different between the two soils.The t test is one of the simplest statistical techniques that is used to evaluate whether there is a statistical difference between the means from up to two different samples. Then, she transfers each of the 20 plants to soil B and measures the mean amount of evaporation for one month. To test this, she measures the mean amount of evaporation for 20 plants in soil A for one month. ![]() Since each car is used in each sample, the researchers can use a paired samples t-test to determine if the mean mpg is different with and without the fuel treatment.Ī botanist wants to know if two different soils lead to different levels of evaporation in plants. To test this, they conduct an experiment in which they measure the mpg of 11 cars with and without the fuel treatment. Researchers want to know if a new fuel treatment leads to a change in the mean miles per gallon of a certain car. Examples: Paired Samples t-tests in Real Life She can use an independent two sample t-test to determine if the mean weight loss is different between the two groups. She then measures the total weight loss of each subject at the end of the month. To test this, she assigns 20 subjects to use diet A for one month and 20 subjects to use diet B for one month. He can use an independent two sample t-test to determine if the mean is different between the two groups.Ī dietician wants to know if two different diets lead to different mean weight loss amounts. He then has each student take the same exam. To test this, he assigns 30 students to use one studying technique and 30 students to use a different studying technique in preparation for an exam. Examples: Independent Two Sample t-tests in Real LifeĪ professor wants to know if two studying techniques lead to different mean exam scores. He can perform a one sample t-test to determine if the mean reduction in blood pressure is significantly greater than the mean reduction that results from the current standard drug. To test this, he recruits 20 subjects to participate in a study in which they each take the new drug for one month. To test this, he measures the mean battery life for 50 products created using the new process and performs a one sample t-test to determine if the mean battery life is different from the mean battery life of products made using the current process.Ī doctor may want to know if some new drug leads to a significant reduction in blood pressure compared to the current standard drug used. Examples: One Sample t-tests in Real LifeĪ manufacturing engineer wants to know if some new process leads to a significant improvement in mean battery life of some product. This article shares several examples of how each of these types of t-tests are used in real life situations. ![]() Paired Samples t-test: Used to compare two population means when each observation in one sample can be paired with an observation in the other sample. Independent Two Sample t-test: Used to compare two population means. One Sample t-test: Used to compare a population mean to some value. In statistics, there are three commonly used t-tests:
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