Conceptual and Philosophical Issues in Psychology - Essay Example

Philosophy of Science of the 2nd December, This paper analyzes how psychology is a science it critically analyzes the core conceptual and philosophical issues relevant to the scientific and statistical nature of psychology. This study explores different approaches that explain why psychology is a science, and why it matters. The study considers classic philosophy of sciences as represented in the views of Popper and Lakatos (1999) and how it applies to psychology. It also considers the basics of statistical inference, comparing the theoretical basis of orthodox as viewed in Neyman Pearson statistics with that of Bayesian statistics. This paper also aims to clear up popular misconceptions encountered while interpreting statistics and their inferences. In the study, a test will be done on how powerful an apology is and forecasting errors in evaluating the value of apology. Apologies are not as adept as people see them. Popper (2002) states apologies are not as strong as people see them as his theory. This theory is a substantial one, and it is being put to test in his work. In this study when people are betrayed by another party, these patterns would falsify the results (a) value of apology will be rated more highly to those who imagine receiving an apology than to those who receive an apology. (b) The wronged party tends to display great trusting behavior when they imagine receiving an apology than receiving an apology. These results show that people are prone to making errors in overvaluing the power of an apology and its effectiveness. The background knowledge that inspires the theory is the effect apologies have on those who have been wronged (Popper, 2002). The background information is that apology is a powerful instrument in people’s lives. The background information, which must be, assumed for the theory to be tested is that apology makes people who are wronged to feel better. The background information is safe because, through the test, the theory will stick that apologies are not as persuasive as people see them and the assumptions will stick to their statements (Dienes, 2008). According to Neyman Pearson, there is a range to determine if the hypotheses are true, and to avoid type 1 error. This means that the null hypothesis is rejected and yet it is the true one. Neyman gives < 0.05 as the range to avoid type 1 errors, for example, in this study case there are three (3) hypotheses, therefore, and their range of rejection would be 0.05/3=0.017. This would reject less than 5% the hypotheses in the long run. This could increase type two errors, therefore, the introduction of sequential Bonferonni procedure which increases accuracy and reduces type 2 errors and family wise errors. In this method assume a number of assumptions to k with p values and order them from the least to the largest. For instance, there are three hypotheses k=3 and their assumed values are P (1) =0 .022 p (2) =0 .024 p (3) =0 .12 A threshold is created where p(1) threshold is 0.05/k p(2)=.05/k-1. P (3)=0.05/k-2. Therefore, P (1) = 0.022_0.05/3=0.017 P (2)=0.024_0.05/2=.025 P (3)=0.12_0.05/1=.05 Starting from the bottom check if the last value is smaller than its threshold p (3) =.12 which is greater than .05. Therefore, reject this hypothesis because it is insignificant. The next value p (2) =.024 and its threshold are .025 which is less than the value, therefore, accept this value and those above it even if their value is greater than their threshold. The reason for accepting the hypothesis is that, there are several tests, which are done, to verify the acceptance and rejection of hypotheses, as opposed to only one test. The Bonferonni procedure is more accurate than the orthodox which does only one test to accept or reject the hypothesis. This results to rejection of true hypothesis or acceptance of the wrong hypothesis which leads to inefficiency. The author establishes sensitivity to pick the differences through the power of confidence, confidence interval, which can be, calculated using the formulae below. SDp squared= 0.5*(SD1 squared + SD2 squared) Power is something decided before running an experiment reason being to decide on the subject number. Cohens d is another method of determining the mean of a related t-test. The author criticizes bonferroni procedure because it does not state how confidence should be increased or reduced. The test in theory one was severe according to Popper (2002) because the entire hypothesis stands their ground. That is they are not refuted all of them with acceptance of only one theory as the true one. The alternative hypotheses are not rejected all them thus making it a severe test. The hard core research that the authors are working on is the continued value given to an apology by people and their continued expectations from those who have offended them. This paper contributes to the research programme in a progressive way. This is because the prediction will be testing a hypothesis in a protective belt which is inspired by hard core and ideally guided by positive heuristic (Lakato & Feyerabend, 1999). According to Bayes procedure mean differences= meandiff, standard error=SE t= meandiff/SE, therefore SE=meandiff/t The Bayes factor is in favor of the null hypothesis as the true hypothesis. The Bayes factor gives ways to test the substantial theories which the t-test does not provide. In conclusion, according to the study and research apology is an essential aspect in today’s generation where people find it hard to live without it. In the study, those who have a high expectation of getting apologies see apology as an exceptional aspect in settling disputes. Apology also increases the trust of those who receive an apology or those expecting to get one (Popper, 2002). For the authors to have a successive test, there must be a substantial theory and alternative theories. To test the theories there must be assumptions or background information which makes the theory to hold. In this paper, errors, which are made, in the aspect of apology are identified where they are tested in the experiment. According to different methods, there are calculations to verify whether a hypothesis should be accepted or rejected. This makes it easy and more accurate than just carrying out only one test. References Dienes, Z. (2008). Understanding Psychology as a Science: An Introduction to Scientific and Statistical Inference. London: Palgrave Macmillan. Lakatos, I. and Feyerabend, P. (1999). For and against method. Chicago: University of Chicago press. Popper, K. (2002). Conjectures and refutations (2nd edition). Delhi: Routledge. Read More