Explanation in Scientific Psychology Chapter 1 PDF

EXPLANATION IN SCIENTIFIC PSYCHOLOGY Chapter 1 Content MAKING SENSE OF THE WORLD SOURCES OF KNOWLEDGE THE NATURE OF THE SCIENTIFIC EXPLANATION What Is a Theory? Induction and Deduction From Theory to Hypothesis Evaluating Theories Intervening Variables THE SCIENCE OF PSYCHOLOGY MAKING SENSE OF...

EXPLANATION IN SCIENTIFIC PSYCHOLOGY Chapter 1 Content MAKING SENSE OF THE WORLD SOURCES OF KNOWLEDGE THE NATURE OF THE SCIENTIFIC EXPLANATION What Is a Theory? Induction and Deduction From Theory to Hypothesis Evaluating Theories Intervening Variables THE SCIENCE OF PSYCHOLOGY MAKING SENSE OF THE WORLD Social Loafing Ringelmann (1913), agricultural engineer, discovered that groups of two pulled at only 95 percent of their capacity, and groups of three and eight sank to 85 percent and 49 percent, respectively. So, it is probably not just our imaginations when we notice others (and ourselves?) seeming to put forth less effort when working in groups: Ringelmann’s research provides us with a good example of social loafing. Latané and his colleagues went on to perform a systematic series of experiments on the phenomenon of social loafing. They first showed that the phenomenon could be obtained in other experimental situations besides that of rope pulling. They also demonstrated that social loafing occurs in several different culture and even holds for young children. Thus, social loafing seems to be a pervasive characteristic of working in groups. People working by themselves think they are responsible for completing the task; when they work in groups, however, this feeling of responsibility diffuses to others. It is an example of psychological research to illustrate how an interesting problem can be brought into a laboratory setting and studied in a controlled manner, and a better understanding of the phenomenon of interest than will simple observation of events and reflection about them. how to develop hypotheses, arrange experimental conditions to test the hypotheses, collect observations (data) within an experiment, and then analyze and interpret the data collected. Curiosity: The Wellspring of Science A scientist wants to discover how and why things work, wants to understand the behaviour. The professional scientist has a strong desire to pursue an observation until an explanation is at hand or a problem is solved. The common denominator for many of these scientific techniques is skepticism.  Skepticism is the philosophical belief that the truth of all knowledge is questionable. No scientific fact can be known with 100 percent certainty. SOURCES OF KNOWLEDGE Fixation of Belief The scientific method is a valid way to acquire knowledge about the world around us. What characteristics of the scientific approach make it a desirable way to learn about and arrive at beliefs about the nature of things? Perhaps the best way to answer this question is to contrast science with other modes of fixing belief, since science is only one way in which beliefs are formed. The scientific method, fixes belief on the basis of experience. Science is based on the assumption that events have causes and that we can discover those causes through controlled observation. This belief, that observable causes determine events, is known as determinism. Let us see what we mean by empirical and self-correcting and examine the advantages associated with those aspects of science. The first advantage of the scientific method is its emphasis on empirical observation. The second advantage of science is that it offers procedures for establishing the superiority of one belief over another. Changing scientific beliefs is usually a slow process, but eventually incorrect ideas are weeded out. THE NATURE OF THE SCIENTIFIC EXPLANATION What Is a Theory? A theory can be crudely defined as a set of related statements that explains a variety of occurrences.  The more the occurrences and the fewer the statements, the better the theory. This does not necessarily mean it is a correct theory, since there are some events it cannot explain. Theory in psychology performs two major functions: o First, it provides a framework for the systematic and orderly display of data— that is, it serves as a convenient way for the scientist to organize data. o Second, it allows the scientist to generate predictions for situations in which no data have been obtained. The greater the degree of precision of these predictions, the better the theory. Sometimes the two functions of theory—organization and prediction—are called description and explanation, respectively. Formulating the roles of theory in this manner often leads to an argument about the relative superiority of deductive or inductive approaches to science. According to the deductive scientist, the inductive scientist is concerned only with description. The inductive scientist defends against this charge by retorting that description is explanation—if a psychologist could correctly predict and control all behavior by referring to properly organized sets of results, then that psychologist would also be explaining behavior. Induction and Deduction Certain basic elements are shared by all approaches to science. The most important of these are data (empirical observations) and theory (organization of concepts that permit prediction of data).  which is more important and which comes first  Modern scientists also emphasize data and view progress in science as working from data to theory. Such an approach is an example of induction, in which reasoning proceeds from particular data to a general theory. The converse approach, which emphasizes theory predicting data, is called deduction; here, reasoning proceeds from a general theory to particular data. One problem with a purely inductive approach has to do with the finality of empirical observations. Scientific observations are tied to the circumstances under which they are made, which means that the laws or theories that are induced from them must also be limited in scope. Theories induced from observations are tentative ideas, not final truths, and the theoretical changes that occur as a result of continued empirical work exemplify the self-correcting nature of science. According to the deductive view, which emphasizes the primacy of theory, well- developed theories in high regard. Casual observations, informal theories, and data take second place to broad theories that describe and predict a substantial number of observations. From the standpoint of the deductive approach, scientific understanding means, in part, that a theory will predict that certain kinds of empirical observations should occur.  But what do correct predictions reveal? If a theory is verified by the results of experiments, a deductive scientist might have increased confidence in the veracity of the theory. However, since empirical observations are not final and can change, something other than verification may be essential for acceptance or rejection of a theory. Popper (1961), a philosopher of science, has suggested that good theories must be fallible; that is, the empirical predictions must be capable of tests that could show them to be false. This suggestion of Popper’s has been called the falsifiability view. According to the falsifiability view, the temporary nature of induction makes negative evidence more important than positive support. If a prediction is supported by data, one cannot say that the theory is true. However, if a theory leads to a prediction that is not supported by the data, then Popper would argue that the theory must be false, and it should be rejected. According to Popper, a theory can never be proven; it can only be disproven. Proctor and Capaldi (2001) have noted two kinds of objections to Popper’s approach. There is a logical problem. Since a theory potentially can always be disconfirmed by the next experiment, the number of accomplished experiments consistent with the theory is irrelevant. So; a well-collaborated theory is not more valuable and does not necessarily make better predictions than a theory that has never been tested. (?) Theories tend to be accepted on the basis of their ability to explain (organize) existing phenomena more than on their ability to predict new results. From Theory to Hypothesis Theories cannot be tested directly. Scientists perform experiments to test hypotheses that are derived from a theory.  But exactly what are scientific hypotheses and where do they come from? It is important to distinguish between hypotheses and generalizations. A hypothesis is a very specific testable statement that can be evaluated from observable data. A generalization is a broader statement that cannot be tested directly. However, it can be used to derive several testable hypotheses. Figure 1.2 illustrates this process. Each generalization can produce more than one hypothesis.  Where do generalizations come from? Figure 1.2 shows there are two sources for generalizations. They can come from theory or from experience. Hypotheses derived from this inductive process are called common-sense hypotheses. Most psychologists prefer testing hypotheses based upon theory. The advantage of a good theory is that it produces many generalizations Evaluating Theories The sophisticated scientist does not try to determine if a particular theory is true or false in an absolute sense. There is no black-and-white approach to theory evaluation. A theory may be known to be incorrect in some portion and yet continue to be used. Although scientists do not state that a theory is true, they must often decide which of several theories is best. As noted earlier, explanations are tentative; nevertheless, the scientist still needs to decide which theory is best for now. To do so, explicit criteria are needed for evaluating a theory. Four such criteria are parsimony precision testability ability to fit data. One important criterion that the fewer the statements in a theory, the better the theory. This criterion is called parsimony, or sometimes Occam’s razor. The principle of parsimony indicates that when 2 theories account for the same facts, the one that is briefer, makes fewer assumptions and references to unobservables, and has the greater generality is to be preferred. Precision is another important criterion, especially in psychology. Theories that involve mathematical equations or computer problems are generally more precise, and hence better, than those that use loose verbal statements. Unless a theory is so precise that different investigators can agree about its predictions, it is for all intents and purposes useless. Testability goes beyond precision. A theory can be very precise and yet not able to be tested because a theory that cannot be tested can never be disproved. At first you might think this would be a good quality since it would be impossible to demonstrate that such a theory was incorrect. The scientist takes the opposite view. This means that theory cannot be evaluated, because only believers can be present when it is demonstrated. The scientist takes a dim view of this logic, and most scientists, especially psychologists, are skeptical about theory. If it is not logically possible to test a theory, it cannot be evaluated; hence, it is useless to the scientist. Finally, a theory must fit the data it explains. It summarizes the size of the differences between the observed data and the theory's expected values. While goodness of fit is not a sufficient criterion for accepting a theory, there is little point in pursuing a theory that fails to fit the data.  Intervening Variables We briefly describe two different kinds of variables in researches. Independent variables are those manipulated by the experimenter. For example, not allowing rats to have any water for several hours would create an independent variable called hours of deprivation. Dependent variables are those observed by the experimenter. For example, one could observe how much water a rat drinks. Science tries to explain the world by relating independent and dependent variables. Intervening variables are abstract concepts that link independent variables to dependent variables. In other words, the outcome of the dependent variable is decided through the intervening variable, which itself gets influenced by the independent variable. An intervening variable is also referred to as mediating variable. When there is no clear or direct relationship present between the independent and dependent variables and their relationship is controlled by some other variable then that variable is considered as mediating variable. When independent variables cannot influence the dependent variable, a mediating variable works as a referee between the two and help us navigate the relationship between independent variables (IV) and dependent variables (DV). In a study on socioeconomic status and reading ability in children, you hypothesize that parental education level is a mediator. This means that socioeconomic status affects reading ability mainly through its influence on parental education levels. Miller (1959) has explained how a single intervening variable, thirst, organizes experimental results efficiently. Figure 1.3 shows a direct and an indirect way to relate an independent variable, hours of deprivation, to a dependent variable, rate of bar pressing. After doing the experiment, we could build a mathematical formula that directly relates hours of deprivation to rate of bar pressing. The indirect method in Figure 1.3 uses two arrows. The first arrow relates hours of deprivation to thirst, an intervening variable. The second arrow relates the intervening variable, thirst, to the rate of bar pressing. Figure 1.4 relates two independent variables, hours of deprivation and feeding dry food, to two dependent variables, rate of bar pressing and volume of water drunk. Direct and in direct explanations are equally complex. Each requires four distinct arrows. Figure 1.5 relates three independent variables, hours of deprivation, feeding dry food, and saline injection to three dependent variables, rate of bar pressing, volume of water drunk, and amount of quinine required to stop the rat from drinking. Again, both direct and indirect explanations are shown. Now, it is obvious that the indirect method is less complicated. It requires six distinct arrows, whereas the direct method requires nine arrows.  So as science tries to relate more independent and dependent variables, intervening variables become more efficient.  THE SCIENCE OF PSYCHOLOGY Psychology and the Real World Scientific research is often divided into two categories: basic and applied. Applied research aims at solving a specific problem whereas basic research has no immediate practical goal. Basic research establishes a reservoir of data, theoretical explanations, and concepts that can be tapped by the applied researcher. Although the division of research into basic and applied categories is common, a far more important distinction is between good and bad research. RESEARCH TECHNIQUES: OBSERVATION AND CORRELATION Chapter 2