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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


Assumptions and philosophies of psychological science

Researchers usually make a number of philosophical assumptions when they approach their discipline, and each discipline has its own set of philosophies and assumptions, including psychology. An awareness of these philosophical assumptions is important because it will help you to understand how the research psychologist approaches his or her work.

Many if not most research psychologists belong to a school of thought called "empiricism." This assumption or philosophy states that our conclusions must be based on observation that is systematic and objective. We reject as evidence such things as anecdotal stories, rumours, or other "data" that canŐt be publicly observed and verified. Furthermore, our observations must be collected using a systematic procedure or set of procedures that can be replicated by others. Note that this does not mean that what we study must be directly observable. For example, we canŐt directly observe how much "anxiety" a person feels, but we can observe how that person behaves (what Ray calls marker variables), including how that person responds to a set of questions related to how anxious he or she feels.
Related to the assumption of empiricism, most psychologists believe that to study something, we must be able to measure it. That is, we must be able to quantify what we are studying. While there is considerable debate as to what is the best way to measure human "things" (such as "love" or "confusion" or "anger" or "guilt"), most accept that nearly anything can be measured in some way. Thus there are few limitations as to what is ultimately within the realm of phenomena suitable for study in psychological science.
The assumption of parsimony states merely that "simpler is better." Given two explanations for the same phenomenon, the one that explains it more simply (while of course still being accurate) is to be preferred. We should not invoke explanations for a phenomenon that is more complex than necessary to adequately describe and predict it.
Falsifiability of Theories and Explanations.
If a theory or explanation isnŐt falsifiable, then it canŐt be properly investigated through psychological science. Psychologists largely reject explanations for behaviour that are not falsifiable. Most of Freudian psychology falls within this realm, as do some interpretations of human behaviour based on evolutionary biology. Most of FreudŐs explanations for psychopathology arenŐt falsifiable. Regardless of the results of a particular study, Freudian theory can explain it, and so Freudian interpretations canŐt be falsified. Similarly, many empirical findings can be explained by spinning a story about evolutionary selection pressures.
The Inexistence of Proof.
It is common to hear people without a strong background in the research process talking about; for example, a study that "proved" such and such, or how proof has been demonstrated for some explanation for behaviour. But in reality, proof doesnŐt exist in the game of science. The progress of science is cumulative. Each study tells a small piece of a big story, while building on previous research that has been conducted. Together, the cumulative research may provide support for a particular explanation more than some other explanation, or may suggest that the explanation is accurate. Usually there are alternative explanations for a single research finding. No single study can prove anything, and even a whole set of studies can only provide support for an explanation or theory. Furthermore, the same data may support more than one explanation. Sometimes the evidence supporting a particular explanation becomes so numerous and compelling that the use of the word "proof" is justified (such as when the corpus of scientific evidence converges on a single conclusion about the relationship between smoking and lung cancer: smoking causes lung cancer). But it is always possible that the explanation or theory is wrong and that, given more data or more research, the data will support an alternative explanation, or one that hasnŐt even yet been offered because no one has thought of it yet. Our knowledge is always evolving and changing. What is "true" now may not be true later.




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