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Sperry 8.1

                 As researchers prepare for their study they must determine what the null hypothesis is. The null hypothesis is either excluded or retained with statistics, and often the opposite of what the researcher believes is true (Erford, 2015). For example, if teens participated in computer-based cognitive therapy (cCBT) to treat depression. The null hypothesis would be that cCBT would not be a primary choice of therapy for teens; as they see no added value when compared to face-to-face therapy.

                The researchers need to address the alternative hypothesis. Alternative hypothesis is the research hypothesis and states what will occur if the null hypothesis is rejected (Eford, 2015). For example, teens who participate in cCBT will find value and continue with treatment, leading to a decrease in depression and anxiety.

                There are two other items that must be addressed within research, statistical and practical significance. Statistical significance is the unlikelihood that the mean differences observed in the sample have occurred due to sampling error (Matheson, Unknown). In the example of cCBT the test was statistically significant between all age groups (Ebert, 2015).

                Practical significance looks at whether the difference is large enough to be of value in a practical sense (Matheson, Unknown). In this example the study showed practical significance. The p-value for the subcategories ranged from .007 to .97 (Ebert, 2015).

Medeiros 8.1

Eighty participants (40 males, 40 females; aged 18-25 years), who were a mixture of students and non-students, were recruited using opportunity sampling. They were recruited using social media, and from psychology classes. All participants were aged between 18- 25 years to reduce the impact of age related differences acting as a potential extraneous variable in the eyewitness memory task (Karpel et al., 2001).

Design A correlational design was used, with the co-variables being: the personality traits derived from the Big 5 models (MacRae & Costa, 1997) and selected from the International Personality Item Pool (2013), e.g. Extraversion, Openness, Agreeableness, Conscientiousness, Neuroticism, and the sub-trait of Neuroticism, Anxiety; and measures of accuracy in an eyewitness memory task, i.e., correct and false recognition scores. Additionally, two multiple regressions were conducted. In these multiple regressions, the personality traits were run as predictor variables, and the recognition scores (both true and false) were conducted as criterion variables.

The current study investigated recognition It is hypothesized: Seven hypotheses were tested, investigating the relationship between personality traits and eyewitness recognition: H1 : Neuroticism will be negatively related to correct eyewitness memory. H2 : Anxiety and Neuroticism will be positively related to false memories. H3 : Conscientiousness will not be significantly related to correct or false recognition. H4 : Neuroticism will be a significant predictor of false eyewitness memory. H5 : Extraversion will have a significant relationship with both correct and false recognition. H6 : Openness will have a significant association with false and correct recognition. H7 : Agreeableness will have a significant link with both false and correct recognition.

The remaining five hypotheses were not supported In sum, only two of the hypotheses were upheld: H3 – Conscientiousness would not be related to either correct or false recognition, as would be expected from previous literature; and H6 – Openness would be associated with correct and false recognition. This latter finding indicated that Openness had a positive relationship with correct recognition, and a negative relationship with false recognition. These relationships had a weak effect size, however, suggesting that these relationships can only be seen when investigated within the specific experimental context, and must thus be interpreted with some caution. The remaining five hypotheses were not supported. (Lee J. Curley, 2017)

what is the difference between statistical significance and practical significance?

The significance level chosen merely specifies the probability of a type 1 error if the null hypothesis is rejected– significance level chosen by the researcher usually is dependent on the consequences of making a type 1 versus a type 2 error– practical significance



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