Observational Studies vs. Experiments
The above video is from: https://www.youtube.com/watch?v=Z_OJzgkKe2A
Above image from http://www.med.uottawa.ca/sim/data/Study_Design_1.jpg
Overview:
Two types of studies that are commonly used in statistics are observational and experimental studies. There are distinct differences between the two types.
Observational Studies:
In this type of study, the sample population is not manipulated, meaning that it is being studied as it is. The researcher does not change or influence the sample population or meddle with the study. Data is gathered by making inferences on what is being observed.
Experimental Studies:
In this type of study, the researcher manipulates the sample population and usually divides the population into a treated group (is experimented on) and a control group (not experimented on) and observes a cause and effect relationship. After conducting the experiment, the researcher is able to re-do the study, changing different aspects to get more accurate results.
Final Reminder:
One major difference that is extremely important is that experimental studies are heavily based on cause and effect. Observational studies can never prove cause and effect relationships.
Examples:
Observational Study
A group of students wanted to know if there is a relationship between attending after school activities and GPA. They then use a survey to gather their data from students who do attend after school activities and who doesn’t attend and ask for their current GPA.
Experimental Study
A group of scientists wanted to test a new drug that’s made to help people suppress their alcohol addiction. The scientists gathers a random population of 200 alcoholics and then divides them into two groups; one receiving the drug and the other a placebo. They then will collect data on if the drug is effective or not.
Two types of studies that are commonly used in statistics are observational and experimental studies. There are distinct differences between the two types.
Observational Studies:
In this type of study, the sample population is not manipulated, meaning that it is being studied as it is. The researcher does not change or influence the sample population or meddle with the study. Data is gathered by making inferences on what is being observed.
Experimental Studies:
In this type of study, the researcher manipulates the sample population and usually divides the population into a treated group (is experimented on) and a control group (not experimented on) and observes a cause and effect relationship. After conducting the experiment, the researcher is able to re-do the study, changing different aspects to get more accurate results.
Final Reminder:
One major difference that is extremely important is that experimental studies are heavily based on cause and effect. Observational studies can never prove cause and effect relationships.
Examples:
Observational Study
A group of students wanted to know if there is a relationship between attending after school activities and GPA. They then use a survey to gather their data from students who do attend after school activities and who doesn’t attend and ask for their current GPA.
Experimental Study
A group of scientists wanted to test a new drug that’s made to help people suppress their alcohol addiction. The scientists gathers a random population of 200 alcoholics and then divides them into two groups; one receiving the drug and the other a placebo. They then will collect data on if the drug is effective or not.