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Chapter 7 - Analysing the Data Part IV - Analysis of Variance Chapter 1 - Behavioural Science and research Chapter 2 - Research Design Chapter 3 - Collecting the Data Chapter 4 - Analysing the Data Part I - Descriptive Statistics Chapter 5 - Analysing the Data Part II - Inferential Statistics Chapter 6 - Analysing the Data Part III - Common Statistical Tests The Scientific Approach The Research Process Variables Confounds The Logic of Cause and Effect Research Hypothesis and Predicition Readings and Links
 

Chapter 1
Behavioural Science and Research

 

Variables

One term that you will hear being used quite frequently is variable. A variable is a concept or construct that can vary or have more than one value. Some variables can be quite concrete such as gender, birth order, weight, or shoe size. Others can be considerably more abstract, vague, and squishy. For exmaple, sense of well being, self-esteem, strength of belief in religion, or IQ. Basically, variables are the things about people that we can say one person has more of than another. So we find that people vary in their gender and shoe size, and their self-esteem and their IQ.

We might then be interested in knowing how certain variables are related to each other. For example, which variables predict self-esteem (itself, another variable). We might be interested in undertsanding the relatiosnhip between self-esteem and variables such as whether or not the person is employed, his or her depression level, the person’s sex, and the number of failed relationships the person has had.

There are two basic kinds of variables that we most often talk about in research. Both Ray and Howell do define these two kinds—what we call the independent variable (IV), and the dependent variable (DV) — although I believe they've failed in their attempt by restricting their definition to a particular kind of study. The independent variable is defined by these authors as the "variable that the experimenter manipulates." While this is true in experiments, not all studies are experiments. Often, we don't manipulate anything in a study. Instead, we merely collect data and observe how variables are related to each other. The text authors’ definition of "independent variable" could imply that there is no independent variable in correlational studies. Similarly, both define the dependent variable as if it were necessarily caused by the independent variable. But this is not necessarily true.

What is the IV and what is the DV changes with the questions being asked. In one sense every variable is a DV until otherwise lined up to be the IV for a particular research question. The independent variable is what we are studying with respect to how it is related to or influences the dependent variable. If the independent variable is related to or influences the dependent variable, it can be used to predict the dependent variable. It is therefore sometimes called the predictor variable, or the explanatory variable. The independent variable may be manipulated or it may just be measured. In contrast, the dependent variable is what we are studying, with respect to how it is related to or influenced by the independent variable or how it can be explained or predicted by the independent variable. It is sometimes called the response variable or the criterion variable. It is never manipulated as a part of the study. DVs are the things we measure about people.

Consider an example. Suppose two investigators are studying the relationship between criminal behaviour in adolescents and parental guidance to determine what kinds of advice to give parents. The two investigators may have the same data. This data includes: (1) the police records of a group of adolescents, giving data about the number of times the child has entered the criminal justice system (such as by being arrested, questioned by the police, etc.), and (2) information from a questionnaire about the kinds of information or advice that each adolescent has received from his or her parents. One investigator might be examining whether parents who give advice focusing on walking away from interpersonal conflicts differ from parents who give advice to the child to "stand up for yourself". The independent variable is the kind of advice the parents give and the dependent variable is whether the child has criminal record or not. But another investigator might be asking a different question. What types of parental advice and guidance distinguishes adolsecents who get itno the criminal system from those that don’t? In this case, whether or not the child has a criminal record or not is the IV and the type of parental advice is the dependent variable. From this example, it should be clear that the distinction between the independent and dependent variable is based not on manipulation but on the questions one is asking of the data.

A useful hint for determining which variable is which in a study is to ask whether you are trying to either influence or predict one variable from some other variable or variables. If so, that variable is probably the dependent variable. The variable that you are using to make the predictions or to determine if it influences (rather than is influenced by) some other variable in the study is typically the independent variable. For this reason, the independent variable is sometimes called the "explanatory" variable while the dependent variable is sometimes called the "response" variable. You try to "explain" variation in responses on the dependent variable with the independent or "explanatory" variable(s).

 

 

 

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