how-to-write-predictions-and-hypotheses-in-psychological-research-reports-65341 [Documents]

This post discusses the topic of predictions in psychological research. The main aim of the post is to provide assistance to researchers who are in the process of writing their predictions in a thesis, lab report, or journal article. The four goals of science are sometimes defined as description, prediction, explanation and control. The scientific imagination often leads to questions like: "I wonder what would happen if we did this?" or "I wonder what is the state of the world?" If our domain-specific knowledge is good we should be able to make accurate predictions. If the phenomena is unpredictable, we should be able to predict properties of the randomness. Prediction serves several purposes. Predictions have various properties. Predictions answer questions about the state of the world. Scientific predictions should be justified. Predictions should have a rationale. The rationale explains why the prediction is made. One type of rationale aims to show why a prediction is accurate. If the prediction is based on theory, evidence may be led about the prior predictive success of the theory and the relevance of the theory to the present circumstances. If the prediction is based on analogy to previous research, evidence may be led about the results of the previous research and the similarities with the present study. A second type of rationale aims to show that the prediction is consistent with assumptions. In particular, if a theory is used to justify a prediction, the relationship between the theory and the predictions need to be clearly and logically articulated. The source of the rationale for a prediction can come from many sources. Common sources include: theory; simulation, common sense; personal belief; hunch; and prior empirical findings. In some settings specific quantitative models can be used to make predictions. For example, in cognitive psychology cognitive architectures such as ACT-R can be used to generate quantitative predictions. A prediction answers a question. Answering questions is the basis of expanding knowledge and represents a common aim of empirical reports. For example, a prediction that the relationship between practice and performance follows a power function is a potential answer to several questions. At the simplest level, it could be rephrased as "is the relationship between practice and performance described well by a power function?" More broadly it could be expressed as "what is the relationship between practice and performance?". Thus, the scientific method of reporting results reiterates ideas through the process of aims, questions, predictions, results, and conclusions. The relationship between the prediction and the nature of the belief can vary. Typically, predictions are presented in such a way that the writing suggests that the researcher finds the prediction plausible. However, researchers can present predictions which they do not believe. A researcher can say that a particular theory would make a given prediction, but that they themselves believe something else. Even when researchers make a prediction that they find persuasive, their strength of belief can vary. This should vary based on the strength of the available evidence. Any prediction leading to an experiment suggests uncertainty. Because if the outcome of the experiment does not have the potential to alter your beliefs, then there is no point in doing it. This content has been created with Essay Writersversion . And such potential suggests uncertainty. Predictions can be distinguished in various ways. Predictions can be expressed at various levels of generality. Operational predictions refer to predictions made in a specific study when the measurements of particular constructs has been set out. Abstract predictions do not specify one or more of the following: context, design, task, types of participant, or measurement approach. For example, the idea that practice improves performance places no explicit limits on how performance is measured, what the task is, who is learning, or what constitutes practice. In general, theories make abstract predictions. These predictions then need to be operationalised using the specific measurement procedure used in the study. The benefits of abstraction is that it reflects a claim of generalisation. The negative side of abstraction is that it introduces ambiguity as researchers differ in their interpretation or in what operationalisations are appropriate. Predictions differ in the degree to which they place constraints on allowable outcomes.