When dealing with data sets it becomes important to eliminate outliers in order to have the most accurate standard deviation. 

Grubbs Test vs. Q Test 

Concept #1: Both tests are useful in detecting a single outlier from a given data set. 

 

Example #1: Wishing to measure the amount of caffeine in a cup of coffee you pour ten cups. From the data provided perform a Q-test to determine if the outlier can be retained or disregarded.

Example #2: White blood cells are the defending cells of the human immune system and fight against infectious diseases. Provided below is the “normal” white blood cell counts for a healthy adult woman. Determine if the current white blood cell count is reasonable by Grubbs test.