Research response 4

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Discussion 1

Extraneous variables are anything in a psychology experiment other than the independent and dependent variables. The variables can present challenges and introduce errors, so it is important for experiments to control these extraneous factors. To control an extraneous variable the researcher needs to begin by identifying those variables that are most likely to influence the dependent variable. This is done based on simple logical reasoning and past experience. For instance, it is common knowledge that noise can be a barrier due to the distractions it can cause hence making data collection to be hard. In that case, one must resort to use a room that is far from a noisy place when doing an interview.

One of the ways through which they can be controlled is by ensuring that they are kept constant across all conditions of the experiment. They can as well be controlled by matching values across treatment conditions. The extraneous variables can be held constant by creating a standardized environment and procedure so that all variables are the same in each condition and therefore cannot be confounding. By matching the values across treatment conditions you are ensuring that the variable does not vary across the treatment conditions, for example participants are assigned so that the average age is the same for all different treatment conditions.


Psychology World (n.d.). Extraneous and Confounding Variables and Systematic vs Non-Systematic Error. Retrieved from

Discussion 2

Extraneous Variables

Extraneous variables exist in all studies and can affect the

measurement of study variables and the relationships among these variables.
Extraneous variables are of primary concern in quantitative studies because
they can interfere with obtaining a clear understanding of the relational or
causal dynamics within these studies. These variables are classified as
recognized or unrecognized and controlled or uncontrolled. Some extraneous
variables are not recognized until the study is in progress or has been
completed, but their presence influences the study outcome.

The extraneous variables that are not recognized until the

study is in process, or are recognized before the study is initiated but cannot
be controlled, are referred to as confounding variables. Sometimes extraneous
variables can be measured during the study and controlled statistically during
analysis. However, extraneous variables that cannot be controlled or measured
are a design weakness and can hinder the interpretation of findings (see
Chapter 8). As control in correlational, quasi-experimental, and experimental
studies decreases, the potential influence of confounding variables increases.

Extraneous variables are any variables that you are not

intentionally studying in your experiment or test. When you run an experiment,
you’re looking to see if one variable (the independent variable) has an effect
on another variable (the dependent variable). In an ideal world you’d run the
experiment, check the results, and voila! Unfortunately…like many things in
life…it’s a little more complicated that than. Other variables, perhaps ones
that never crossed your mind, might influence the outcome of an experiment.
These undesirable variables are called extraneous variables.

A simple example: you want to know if online learning

increases student understanding of statistics. One group uses an online
knowledge base to study, the other group uses a traditional text. Extraneous
variables could include prior knowledge of statistics; you would have to make
sure that group A roughly matched group B with prior knowledge before starting
the study. Other extraneous variables could include amount of support in the
home, socio-economic income, or temperature of the testing room.

Types of Extraneous Variables

Demand characteristics: environmental clues which tell the

participant how to behave, like features in the surrounding or researcher’s
non-verbal behavior.

Experimenter / Investigator Effects: where the researcher

unintentionally affects the outcome by giving clues to the participants about
how they should behave.

Participant variables, like prior knowledge, health status

or any other individual characteristic that could affect the outcome.

Situational variables, like noise, lighting or temperature

in the environment.

One type of extraneous variable is called a confounding

variable. Confounding variables directly affect how the independent variable
acts on the dependent variable. It can muddle your results, leading you to
think that there is cause and effect when in fact there is not. In the above
example, a confounding variable could be introduced if the researcher gave the
text book to students in a low income school, and assigned online learning to
students in a higher income school. As students in higher income schools
typically take more challenging coursework than students in lower income
schools, pre-knowledge becomes a confounding extraneous variable.

Extraneous variables should be controlled if possible. One

way to control extraneous variables is with random sampling. Random sampling
does not eliminate any extraneous variable, it only ensures it is equal between
all groups. If random sampling isn’t used, the effect that an extraneous
variable can have on the study results become a lot more of a concern.


Grove, S., Gray, J., Burns, N. (2015). Understanding Nursing

Research, 6th Edition. [Pageburstl]. Retrieved from…

Extraneous Variable Simple Definition. (n.d.). Retrieved

April 16, 2018, from…

Discussion 3

Extraneous variable is basically an extra variable. Not knowing or having that extra variable could counteract the result. By controlling one must be aware these exist or it could influence the outcome of the experiment. Extraneous variables are usually something the researcher doesn’t have control over such as external sounds and characteristics of individualsWhen running an experiment, one looks to see if one variable (independent variable) has an effect on another variable (dependent variables). They have the ability to affect the relationship between independent and dependent variables. The undesirable variables are known as extraneous variables and add errors to an experiment. “They are found in all studies, however, with unequal degrees of desire. If a researcher is able to recognize the presence of such prior to initiating the study, they may be able to design the study that any effects on the outcome are mitigated. If not recognized or controlled, they are considered weaknesses and degrade the internal validity of the study.” Grove, Gray & Burns, (2015).

There are four types:

1. Demand characteristics: Environmental clues which tell the participate how to behave, like features in the surrounding or researcher’s non-verbal behavior

2. Experimenter/Investigator Effects: Where the researcher unintentionally affects the outcome by giving clues to the participates about how they should behave

3. Participate variables: Health status or any other individual characteristic that could affect the outcome.

4. Situational variables: External noise, temperature and weather in an environment.

In order to control the extraneous variable the researcher must recognize those variables that could affect the dependent variable. Here’s an example. My concentration level is little to none when the TV is now. The TV is my extraneous variable which when removed or turned off I lose this variable thus improving my focus at hand Daily yogi has been proven to decrease anxiety. However, what is my sample? Ages difference, gender type, stress level, type of diet or death of a family member are all factors of my sample study/experiment..


Grove S. K., Gray, J. R., & Burns, N., (2015). Understanding nursing research (6thed.) St Louis, MO: Elsevier.

Nwachukwu, C. P., (2017). Extraneous Variable Simple Definition.Statistics How To.

Discussion 4

Extraneous variables are any variables that you are not intentionally studying in your experiment or test. A type of variable to be aware of when reading or designing studies (Kleinbaum et al., 1982; 1998; Polit et al., 2001). So it is vital for researchers to identify any potential extraneous variables and try to control them because they can influence the relationship between the variables that an experimenter is examining, or indicate there is a causal relationship between them when none exists, and also affect the result of the research. There are different types of extraneous variables and they are called undesirable variables. How could a researcher attempt to control these variables?. Researchers try to control for extraneous variables in their experiments by controlling the conditions of the experimental environment to keep variables as constant as possible (Polit et al., 2001). If experimental control is not possible, the researcher has three options for dealing with extraneous variables (Polit et al., 2001):

1- One way is to try to match the study participants on the possible confounds, such as matching experimental and control subjects, or cases and noncases, by age, gender, and other key possible confounding Variables .

2- . Another way is to incorporate an extraneous variable as an independent variable in the study design. If age, for example, might have an effect on the relationship between the independent variable and dependent variable, the researcher can group participants into subgroups of different ages. This method is called ‘‘stratification,’’ and the ‘‘effects’’ of stratified variables are usually included in the statistical analyses (Mausner & Kramer, 1985).

3- The third way is to use the person’s age as an independent variable in the statistical analyses. It is a common practice to measure an extraneous variable and include the measure of it only in the statistical analysis as a way to control for variation in the levels of the variable among the study’s participants. This practice is particularly common in survey studies.

Regardless of the approach used to control extraneous variables, it is always important to see if the participants vary in ways that could affect the dependent variable.


Kleinbaum, D. G., Kupper, L. L., & Morgenstern, H. (1982). Epidemiologic research:

Principles and quantitative methods. New York, NY: Van Nostrand Reinhold. Retrieved


methods /oclc/13518922, April 16,2018.

Laura T. Flannelly, Kevin J. Flannelly & Katherine R. B. Jankowski (2014) Independent,

Dependent, and Other Variables in Healthcare and Chaplaincy Research, Journal of Health

Care Chaplaincy, 20:4, 161-170, DOI: 10.1080/08854726.2014.959374. Retrieved from, April 16,2018.

.Mausner, J., & Kramer, S. (1985). Epidemiology: An introductory text (2nd ed.). Philadelphia,

PA: W.P. Saunders .Retrieved from

April 16, 2018.

Polit, D. F., Beck, C. T., & Hungler, B. P. (2001). Essentials of nursing research: Methods,

appraisal, and utilization (5th ed.). New York, NY: Lippincott. DOI:. 10.7748/nr.13.4.91.s11.

Retrieved from April 16,2018.

Discussion 5

When performing research, the researcher analyzes data on independent variables and their effects on the dependent variable. But sometimes, undesirable variables occur. These variables are referred to as extraneous variables. According to Wienclaw extraneous variables are (2013), variables that affect the outcome of the experiment (i.e., whether or not the people questioned like the new interface) that have nothing to do with the independent variable itself. There are four types of extraneous variables. They include; demand, researcher effect, participant variables and situation variables. Demand refers to clues that are either environmental or non-verbal researcher clue of behavior. Researcher effect is an unintentional behavior clue from the researcher. Participant variables include prior knowledge of experiment health status or other characteristics that could skew data collection. Environmental variables are related to room temperature, lighting or noise to name a few. These variables can lead to errors with research and need to be controlled. It can be difficult to control all various, but good research controls as many extraneous variables as it can. One way researchers can attempt to limit these errors is using random sampling. By using random sampling, this will ensure the groups are equal. Weinclaw’s article discusses control of the data (2013), although is impossible to control for every possible extraneous variable, the more of these that are accounted for and controlled in the experimental design, the more meaningful the results will be.

Stephanie (2017). What are extraneous variables. Statistics how to. Retrieved from

Weinclaw, R. (2013). Statistical principles for problem solving. Research starters: business. (online edition). Retrieved from EBSCO.

Discussion 6

Researchers use many ways to true to valid experiments and to control extraneous variables. One way that researchers can be in control is by planning out what they want the outcome to be in the research. They can do this by keeping the experiments or subjects the same. He could have all one age or all female or male to limit different outcomes. Complete control cannot be guaranteed but with careful planning it can be close. Most experiments conducted by educational researchers are quasi experiments (Borg and Gall, 1989). With this type of research the subjects are randomly assigned to groups and gives the researcher a greater chance to control the variables. It is unlikely to achieve this type of control in a classroom setting as you would in the laboratory. According to (Kennedy and Bush, 2001) they say that if the researcher have confident that the results are the effect of the treatment and not an extraneous agent than control is gained but only if they are confident that the results were from treatment. When the experiment cannot be controlled it is said that the researcher cannot be confident in the results and control is not gained.


Borg, W. R. and Gall, M.D. (2001). Educational Research: An Introduction, Fifth Edition Retrieved from…

Kennedy, T. J. and Bush, A.J. (n.d). An Introduction to Experiment and Behavioral Research. Retrieved from…