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Chapter 4

PsyB01 Chapter 4.doc

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Connie Boudens

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Chapter 4 – Studying Behaviour Intro to validity • Construct validity: concerns whether our methods of studying variables are accurate • Internal validity : refers to the accuracy of conclusions about cause and effect • External validity: concerns whether we can generalize the findings of a study to other settings Variables - A variable is any event, situation, behaviour, or individual characteristic that varies - Each variable represents a general class within which specific instances will vary; these specific instances are called the levels or values of the variable - Variables can be classified into four general categories: o Situational variables describe characteristics of a situation or environment o Response variables are the responses or behaviours of individuals, such as reaction time and performance on a cognitive task o Participant or subject variables, are individual differences; these are the characteristics of individuals, including gender, intelligence and personality traits o Mediating variables are psychological processes that mediate the effects of a situational variable on a particular response  For example, a mediating variable would be diffusion of responsibility, which is when there are several bystanders, personal responsibility to help is diffused among all the bystanders, so no single person feels much responsibility Operational Definitions of Variables - The operational definition of a variable is a definition of the variable in terms of the operations or techniques the researcher uses to measure or manipulate it - Variables must be operationally defined so they can be studied empirically - The task of operationally defining a variable forces scientists to discuss abstract concepts in concrete terms; the process can result in the realization that the variable is too vague to study - This realization does not necessarily indicate that the concept is meaningless, but rather that systematic research is not possible until the concept can be operationally defined - Once an operational definition is found, progress in understanding a psychological phenomenon is often dependent on the development of increasingly sophisticated technology - Operational definitions also help us communicate our ideas to others - There is rarely a single, infallible method for operationally defining a variable; researchers must decide which one to use given the particular problems under study, the goals of the research, and other considerations such as ethics and costs Relationships between Variables - The relationship between two variables is the general way in which the different values of one variable are associated with different values of the other variable - When both variables have values along a numeric scale, many different “shapes” can describe the relationship: o The positive linear relationship o The negative linear relationship o The curvilinear relationship o The situation in which there is no relationship between the variables Positive Linear Relationship - In a positive linear relationship, increases in the values of one variable are accompanied by increases in the values of the second variable Negative Linear Relationship - In a negative linear relationship, increases in the values of one variable are accompanied by decreases in the values of the other variable - Social loafing is a phenomenon where as the number of people working a on a task increases, the group effort and productivity may actually decreases Curvilinear Relationship - In a curvilinear relationship, increases in the values of one variable are accompanied by both increases and decreases in the values of the other variable - In other words, the direction of the relationship changes at least once; this type of relationship is sometimes referred to as a nonmonotonic function (e.g. an inverted-U shape function) No Relationship - When there is no relationship between the two variables, the graph is simply a flat line - Unrelated variables vary independently of one another - The positive and negative linear relationships are example of a more general category of relationships described as monotonic because the relationship between the variables is always positive or always negative (it does not change directions) - Individual deviations from the general pattern are likely - Correlation coefficient is a numerical index of the strength of relationship between variables, which is important because we need to know how strongly variables are related to one another Relationships and Reduction of Uncertainty - When we detect a relationship between variables, we reduce uncertainty about the world by increasing our understanding of the variables we are examining - The term uncertainty implies that there is randomness in events; scientists refer to this as random variability or error variance in events that occur in the world - Research is aimed at reducing random variability by identifying systematic relationships between variables Nonexperimental versus Experimental Methods - There are two general approaches to the study of relationships among variables: o With the nonexperimental method, relationships are studied by making observations or measures of the variables of interest; that is, behaviour is observed as it occurs naturally (e.g. directly observing behaviour, asking people to describe their behaviour) o The experimental method involves direct manipulation and control of variables; the researcher manipulates the first variable of interest and then observes the response  With this method, the two variables do not merely vary together; one variable is introduced first to see whether it affects the second variable Nonexperimental Method - Because the nonexperimental method allows us to observe covariation between variables, another term that is frequently used is the correlational method; with this method, we examine whether the variables correlate or vary together - However, there is a weakness of this method when we ask questions about cause and effect - There are two problems with making causal statements when the nonexperimental method is used: o It can be difficult to determine the direction of cause and effect o The third-variable problem – that is, extraneous variables may be causing an observed relationship Direction of Cause and Effect - With the nonexperimental method, is it difficult to determine which variable causes the other - Knowledge of the correct direction of cause and effect in turn has implications for applications of research findings - However, the direction of cause and effect is often not crucial because, for some pairs of variables, the causal pattern may operate in both directions The Third-Variable Problem - When the nonexperimental method is used, there is the danger that no direct causal relationship exists between the two variables - The third-variable problem is any variable that is extraneous to the two variables being studied; any number of other third variables may be responsible for an observed relationship between two variables - The third variable is an alternative explanation for the observed relationship between the variables - The ability to rule out alternative explanations for the observed relationship between two variables is an important factor when we try to infer that one variable causes another - Direction of cause and effect and potential third variables represent serious li
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