Independent, Dependent and Confounding Variables in Quantitative Research

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• published: 17 Jan 2014
• views: 49104

http://youstudynursing.com/ Research eBook on Amazon: http://amzn.to/1hB2eBd Check out the links below and SUBSCRIBE for more youtube.com/user/NurseKillam Related Videos: http://www.youtube.com/playlist?list=PLs4oKIDq23AdTCF0xKCiARJaBaSrwP5P2 Connect with me on Facebook: https://www.facebook.com/NursesDeservePraise Twitter: @NurseKillam https://twitter.com/NurseKillam Research questions should clearly identify the variables under study. In the above examples X symbolizes the independent variable and Y symbolizes the dependent variable. In this video we are going to examine the question "Is there a difference in GPA between nursing students who watch NurseKillam's videos and those who do not watch NurseKillam's videos?" The independent variable is the one that researchers think will have an effect on the dependent variable or variables under study. If the study is experimental the researcher will manipulate this variable. This manipulation means that the researchers will cause the variable to happen in a group of people. For example, if we used our question for an experimental study the researcher would show NurseKillam's videos to one group of students while ensuring that the other group of students did not see them. If the study is non-experimental the variable is assumed to happen naturally before or during the study. Instead of making some students watch the videos the researchers would measure or observe if the videos were watched. One way to do this would be to survey students to see if they had watched the videos. Like the name suggests, the dependent variable is assumed to be a result of or change based on the presence, absence or magnitude of the independent variable. One way to remember this relationship is that the outcome of the dependent variable depends on the independent variable. The question is worded in a way that identifies the variables to be studied. In our example the two variables are GPA and watching NurseKillam's videos. It would not make sense for an increased GPA to cause students to watch the videos. However, watching the videos may cause an increase a student's GPA. Therefore, the dependent variable in our example is the GPA. The one that is assumed to cause the change in the GPA is the independent variable. Even though a higher GPA may be assumed to be a result of watching NurseKillam's videos a causal relationship between the two variables cannot necessarily be proven. Instead, a relationship can be identified but awareness of other factors needs to be discussed. When examining the relationship between the independent and dependent variables researchers must also be aware of and control for as many confounding variables as possible. Confounding variables include anything that may confuse or confound the relationship that is being examined. It is because of confounding variables that non-experimental research cannot prove cause and effect relationships. Researchers also need to be careful not to claim cause and effect relationships too easily in experimental research because of these confounding variables. In experimental research an attempt is made to control as many confounding variables as possible. In our example question, what things other than watching NurseKillam's videos may cause an increased GPA? Anything other than the independent variable that could have caused the student's GPA to increase would be a confounding variable. To remember what these types of variables are and how to identify them think about relationships. The dependent variable is the one that depends on something and is expected to change. Independent variables, like independent people do not rely on others. Anything that may confuse this relationship is confounding. There are a couple of messages I want you to take from this example: 1) Please note that research questions may include many variables -- not just one independent and one dependent variable. 2) whether a particular variable like class attendance is independent or dependent may change depending on the role it plays in any given study.

Independent, Dependent and Confounding Variables in Quantitative Research

• Report rights infringement
• published: 17 Jan 2014
• views: 49104

http://youstudynursing.com/ Research eBook on Amazon: http://amzn.to/1hB2eBd Check out the links below and SUBSCRIBE for more youtube.com/user/NurseKillam Related Videos: http://www.youtube.com/playlist?list=PLs4oKIDq23AdTCF0xKCiARJaBaSrwP5P2 Connect with me on Facebook: https://www.facebook.com/NursesDeservePraise Twitter: @NurseKillam https://twitter.com/NurseKillam Research questions should clearly identify the variables under study. In the above examples X symbolizes the independent variable and Y symbolizes the dependent variable. In this video we are going to examine the question "Is there a difference in GPA between nursing students who watch NurseKillam's videos and those who do not watch NurseKillam's videos?" The independent variable is the one that researchers think will have an effect on the dependent variable or variables under study. If the study is experimental the researcher will manipulate this variable. This manipulation means that the researchers will cause the variable to happen in a group of people. For example, if we used our question for an experimental study the researcher would show NurseKillam's videos to one group of students while ensuring that the other group of students did not see them. If the study is non-experimental the variable is assumed to happen naturally before or during the study. Instead of making some students watch the videos the researchers would measure or observe if the videos were watched. One way to do this would be to survey students to see if they had watched the videos. Like the name suggests, the dependent variable is assumed to be a result of or change based on the presence, absence or magnitude of the independent variable. One way to remember this relationship is that the outcome of the dependent variable depends on the independent variable. The question is worded in a way that identifies the variables to be studied. In our example the two variables are GPA and watching NurseKillam's videos. It would not make sense for an increased GPA to cause students to watch the videos. However, watching the videos may cause an increase a student's GPA. Therefore, the dependent variable in our example is the GPA. The one that is assumed to cause the change in the GPA is the independent variable. Even though a higher GPA may be assumed to be a result of watching NurseKillam's videos a causal relationship between the two variables cannot necessarily be proven. Instead, a relationship can be identified but awareness of other factors needs to be discussed. When examining the relationship between the independent and dependent variables researchers must also be aware of and control for as many confounding variables as possible. Confounding variables include anything that may confuse or confound the relationship that is being examined. It is because of confounding variables that non-experimental research cannot prove cause and effect relationships. Researchers also need to be careful not to claim cause and effect relationships too easily in experimental research because of these confounding variables. In experimental research an attempt is made to control as many confounding variables as possible. In our example question, what things other than watching NurseKillam's videos may cause an increased GPA? Anything other than the independent variable that could have caused the student's GPA to increase would be a confounding variable. To remember what these types of variables are and how to identify them think about relationships. The dependent variable is the one that depends on something and is expected to change. Independent variables, like independent people do not rely on others. Anything that may confuse this relationship is confounding. There are a couple of messages I want you to take from this example: 1) Please note that research questions may include many variables -- not just one independent and one dependent variable. 2) whether a particular variable like class attendance is independent or dependent may change depending on the role it plays in any given study.