Psychology Article Example | Topics and Well Written Essays - 1000 words

Psychology - Article Example Summarizing the data also involves the determination of significance of the results, which means that the data gathered from the investigation did not simply happen by chance. Significance also reflects the robustness of the data gathered from the research study. Summarizing the data also allows the researcher to find any patterns, trends and motifs that are commonly observed during a particular situation such as that investigated in the study. On the other hand, the process of confirming the data involves the validation of the hypotheses of the study. Based on the information gathered from the investigation, as well as the analysis performed for robustness and significance, it is possible to know whether the initial hypothesis should be accepted or refuted. Confirming data thus allows the researcher judge the information that was collected from the investigation. This process also provides a way for the investigator to determine whether the results are indeed credible, as evidenced by the statistical tests that were performed when the data was being summarized. The processes of summarizing and confirming the data are two separate steps generally employed in research investigations yet each is highly dependent on the other. It is thus important to perform both steps in sequence in order to attain a highly reliable research output. b. The Null Hypothesis Significance Testing allows the researcher to determine whether the results obtained from the investigation was truly based on the effects of the variables being studies. The most important component of a research investigation is the formulation of the hypotheses that would serve as the basis of the investigation. In most studies, a certain association or correlation is identified as a research topic of interest, such as that of the effect of a particular scenario that results in a specific response. The null hypothesis is regarded as a type of hypothesis that states that there is no association or correlation between two variables. On the other hand, the alternative hypothesis describes the opposite of the null hypothesis, wherein there is indeed a correlation or association between the two variables. In order to determine whether the null hypothesis should be accepted or rejected, it is thus important to test the data gathered from the investigation using statistical tests such as the t-test or the chi-square test. These tests allow the researcher to determine that the data gathered were not generated simply by chance. These tests allow the calculation for P values, which represent the significance of the results. A significant result would show a P value of at least 0.05, which shows that 95% of the time a certain pattern will be observed if the experiment is repeated using the same settings. For example, the administration of an anti-depressant drug is hypothesized to result in the alleviation of depression symptoms in a patient. The null hypothesis of this study would state that the administration of the drug would not result in the alleviation of the symptoms. The alternative hypothesis, on the other hand, would result in the alleviation of the symptoms. If the study populati on experienced a better condition after taking the drug, then a Type I error or rejection of the null hypot