What single subject design can establish the existence of a cause and effect relationship?
Experimental research designs that use the results from a single participant or subject to establish the existence of a cause-and-effect relationship. Also known as single-case designs. In a single-subject research study, observations or measurements made while no treatment is being administered.
Is any characteristic that can vary such as age weight or height?
Any characteristic, which varies from individual to individual is called a variable (1). The characteristics such as age, sex, height, weight, body mass index (BMI), blood group, body temperature, blood glucose level, blood pressure, heart rate, number of teeth, severity of disease (mild, moderate, severe) etc.
Which of the following behaviors would most likely be interested in robotics because of its focus on mechanistic aspects of behavior?
Psychology of Learning Ch. 1 & 2
|Which behaviorist would be most interested in robotics, because of its focus on mechanistic aspects of behavior?||Hull|
|A mental representation of one’s surroundings is a ___.||cognitive map|
Which of the following is used to reduce effects of confounding variables?
There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization. In restriction, you restrict your sample by only including certain subjects that have the same values of potential confounding variables.
How do you handle confounding variables?
Strategies to reduce confounding are:
- randomization (aim is random distribution of confounders between study groups)
- restriction (restrict entry to study of individuals with confounding factors – risks bias in itself)
- matching (of individuals or groups, aim for equal distribution of confounders)
What are confounding variables and what problems can they cause?
Since a confounding variable is a 3rd factor that is not accounted for in a research process, it can affect an experiment by producing inaccurate research results. For example, it can suggest a false correlational relationship between dependent and independent variables.
Is intelligence a confounding variable?
A confounding variable is an extraneous variable that differs on average acrosslevels of the independent variable. For example, in almost all experiments, participants’ intelligence quotients (IQs) will be an extraneous variable. In this case, IQ would be a confounding variable.
How do you test for confounding variables?
Identifying Confounding A simple, direct way to determine whether a given risk factor caused confounding is to compare the estimated measure of association before and after adjusting for confounding. In other words, compute the measure of association both before and after adjusting for a potential confounding factor.
What do confounding variables affect?
A confounding variable is an outside influence that changes the effect of a dependent and independent variable. This extraneous influence is used to influence the outcome of an experimental design. Confounding variables can ruin an experiment and produce useless results.
What are common confounding variables?
A confounding variable is an “extra” variable that you didn’t account for. They can ruin an experiment and give you useless results. They can suggest there is correlation when in fact there isn’t. Confounding variables are any other variable that also has an effect on your dependent variable.
Is age a covariate?
So there are two options. One is to conceptually rule out effects of age (e.g., by showing that the age difference between groups is either not in the direction that would cause the expected difference in your DV, or is too small to cause a difference), the other is to include age as a covariate; same goes for gender.
What is the difference between extraneous and confounding variables?
Extraneous variables are those that produce an association between two variables that are not causally related. Confounding variables are similar to extraneous variables, the difference being that they are affecting two variables that are not spuriously related. …
Is age a confounding or extraneous variable?
An extraneous variable becomes a confounding variable when it varies along with the factors you are actually interested in. To return to the example, age might be an extraneous variable. The researchers could control for age by making sure that everyone in the experiment is the same age.
Is time of day a confounding variable?
This third variable could be anything such as the time of day or the weather outside. In this situation, it is indeed the weather that acts as the confound and creates this correlation.
How do you find extraneous variables?
Extraneous variables are all variables, which are not the independent variable, but could affect the results of the experiment. The researcher wants to make sure that it is the manipulation of the independent variable that has an effect on the dependent variable.
What is meant by control of extraneous variables?
One way to control extraneous variables is to hold them constant. This technique can mean holding situation or task variables constant by testing all participants in the same location, giving them identical instructions, treating them in the same way, and so on. It can also mean holding participant variables constant.
Is demand characteristics an extraneous variable?
Typically, demand characteristics are considered an extraneous variable, exerting an effect on behavior other than that intended by the experimenter. Demand characteristics cannot be eliminated from experiments, but demand characteristics can be studied to see their effect on such experiments.
Why do demand characteristics affect internal validity?
Demand characteristics occur when the participants try to make sense of the research and act accordingly to support the aim of the research. Demand characteristics are a issue, as the participants may behave in a way to support the hypothesis, making the results less valid.
What is an extraneous variable example?
Situational Variables: These extraneous variables are related to things in the environment that may impact how each participant responds. For example, if a participant is taking a test in a chilly room, the temperature would be considered an extraneous variable.