Psychology Research Analysis Report Writing Assessment Answer

Psychology Research Analysis Report Writing Assignment

In your professional lives, during the course of a research project you will often know the researchers, participants or confederates in your study. If such a situation arises, as a professional it is important that you proceed ethically. Some ways in which you can do this include:

1. De-identifying all data. Never refer to anyone by name - this includes the

names of Institutions (e.g., Schools or Clinics). 2. Report group data, not individual scores. For example, “The group mean

was..” or “The mean for males was..” etc. 3. Always write using formal academic language. In the third person and

past tense is preferable.

For instance, you may find yourself as part of a mental health team that decides to write a paper comparing the treatment regimes of a group of clients with phobias. At your clinic, Dr Smith is treating clients with phobias using a Cognitive Behavioural Intevention whilst Dr Brown is implementing a Meditation/Visualisation technique. Your clinic is located in Springmeadow, Sydney, and is called The Royal Phobia Treatment Centre. Over the course of the year, you as the Centre Director, get to know most of the clients by name.

In this example, any information that could identify the clinic, the practitioners, or most importantly the clients, would be removed or generalised. Therefore, when situating the study, you would refer to the clinic in general terms, for example, a phobia treatment clinic in Sydney, Australia. Likewise, the clinicians themselves would not be named, instead the treatment groups would be referred to collectively as the CBT Group and the MV Group (if necessary the practitioners may also be referred to as Clinician A and Clinician B). You would talk about the study in the third person and not identify yourself as the Director of the clinic or by name. Instead, if required you would state, “The aim of the current research..” or “It is predicted that...” etc. Not “Director Jones predicts that...”

In relation to the clients themselves, no names would be used and only general demographics provided (e.g., descriptive statistics on age and/or gender). A range of phobia test scores (including minimum and maximum scores) for each group may be necessary, but there should be no way of identifying which clients specifically obtained those minimum and maximum scores.

In our research example, though Summertown High is clearly a fictitious school and it has been fun (and often amusing) learning about the different predicaments of the staff and students, when it comes to conducting our assessment research, we must be both professional and ethical. Therefore as practice for the real-world, you will follow the same standards for our fictitious scenario, as you would if you were the member of any research project. This means following the three steps indicated above and you may use the clinic example provided in this document for guidance.

You may however take some artistic license and assume Summertown High is a Selective State High School located in Sydney, Australia.

Introduction

• 2.0 Last paragraph of introduction

The recent increase in student unruliness behaviour has caused a lot of concern. From past research and literature available, the colour yellow has linked with creating restlessness and sensations of fatigue. The response of the students on the self assessment plus the other data collected will tell us with certainty whether the yellow colour that was painted on the classroom walls as part of the refurbishment can be blamed for the increase in cases of classroom unruliness that has been witnessed recently. Therefore, this study will establish whether painting yellow colour on classroom walls can lead to classroom unruliness by causing frustration and anger among students

• 2.1 Participants and materials

For this experiment one control sample was used against one testing sample. The control room was painted a less saturated colour which was a relaxing shade of green referred to as Apple Delight. The test room was one random yellow-painted classroom. The population being tested consisted of students from junior school. The size of the sample in the classroom that was painted the relaxing shade of green was 25 while the size of the sample being tested was 24. A questionnaire that was admitted to students from both samples to collect data on the levels of anger as well as levels of liking of the colours painted on the classroom walls that the students experienced.

• 3.0 Design and procedure

Observation was the main tool of collecting data, although other techniques were also applied where necessary. The sample sizes were limited to n = 24 and n = 25 for the test and control samples respectively. A questionnaire was designed to conduct a self-assessment of the liking of room colour by the students as well as assess their current levels of anger. Observation was used to make a subjective judgment on the aggressive behaviour of students in the control sample (classroom painted relaxing shade of green). This observation was conducted over a 45-minute normal classroom session. The assessment of the aggressive behaviour was determined on a scale of 1 to 50. A similar procedure was used to assess the aggressive behaviour of students from both samples, but the sample being tested, the sample size was 24 while the control sample size was 25. Final determination of the “level” of the unruliness of a student in classroom behaviour was based on a simple addition of the scores of aggressive behaviour (out of 50) and their scores on liking of the room colour (out of 50). This determination was evaluated in a similar manner across both rooms. This is the data that were analysed to determine whether yellow colour on classroom walls leads to aggressive behaviour by causing frustration and anger.

• 4.0 Results

Results of Regression Analysis, determining the Effect of the yellow colour of classroom walls on student unruliness (anger, aggressiveness and liking) is as shown in Appendix 1. According to the regression results, it indicates that unruliness and frustration accounted for 73.1% of the variation in classroom colour (R2 = 0.731). The un-standardized beta coefficients indicate that anger (? = 0.073, p < 0.01), aggressiveness (? = 0.237, p < 0.01), liking and (? = -0.110, p < 0.01) were strongly predicted by the yellow colour on the classroom walls. The ANOVA in appendix shows

• 5.0 Discussion

The results of the regression suggest that, classroom yellow colour influence unruliness (anger, aggressiveness and liking). Therefore, the null hypothesis which stated that there was no statistically significant relationship between unruliness (anger, aggressiveness and liking) on classroom yellow colour was rejected and the alternative hypothesis which states that there was a statistically significant relationship between unruliness (anger, aggressiveness and liking) on classroom yellow colour was accepted. According to the findings of this study, classroom yellow colour influence unruliness of students. Thus anger, aggressiveness and liking will be high in students who are in classrooms painted with yellow colour.

• 6.0 PART 2

• 6.1 Research design flaws

First, the choice of the control sample was not representative enough of the null hypothesis. The relaxing shade of green could have a different effect on the sample population that may coincidentally be interpreted as a relaxing sensation. A wider sample, for example, two or more classrooms painted with different colours that are considered relaxing, would definitely have confirmed beyond all doubt that yellow is the problem. However, as samples were chosen, it might not have been sufficient enough to make a firm conclusion on the hypothesis that was being tested.

Secondly, the subjecting of the students to a self assessment did not exhibit independence in the collection of data on the liking of room colour. Taking into consideration the characteristics and nature of the sample population and sample population being confined together during the collection of the data, there was a high chance of occurrence of cross-sample influences. This is to say, the values collected for the characteristic being measured (liking of the room) could have been a misrepresentation of the actual values due to a student wanting to respond how their peers have responded.

Third, the range of scores for evaluating aggressive behaviour and level of anger is too wide for such a continuous type of data. For example, it would be nearly impossible to distinguish an aggressive behaviour that would score 21 from that that would score 22. A shorter range for this type of characteristic would be more appropriate.

Lastly, the addition of the two variables as an overall determination of student unruliness was completely wrong. In the hypothesis being tested, one variable (the level of anger) leads to the other (unruliness). Therefore, it is illogical to add the values the first and second variables to determine the value of the second.

• 7.0 PART 3

• 7.1 Question1

I would use factorial regression and Analysis of variance to analyse data from this design. This is because when more than two discrete outcomes are expected multinomial logistic regression can efficiently generalise logistic regression to such problems with more than two discrete outcomes plus analysis of variance would show the variations in the reactions vis-a-vis the colours (Mandel, 2012).

• 7.2 Question2

1. a) History effects refer to factors that are not within the experiment; that may potentially bias responses to experimental procedures (Kable & Coles, 2015). History effects are not likely to bias responses in a closed-environment experiment such as this one (O'Rourke, Psych & Hatcher, 2013).
2. b) Maturation effects refer to changes, such as growth, that can occur in the population in the duration of the experiment and change the subjects' reactions to the independent variables (Campbell & Stanley, 2015). Maturation effects in this experiment can be ruled out as a threat to the validity of the outcomes of the experiment.
3. c) Mortality effects are errors caused by making inferences by using only the population that goes through to the end of the experiment (Guo & Fraser, 2014). Mortality effects can be ruled out here since the entire population of the samples participated in the entire program. According to Stevens (2012) mortality effects leave inadequate explanations for differences in the outcomes.
4. d) Regression to the mean refers to a selection of the population on the extremes (Soini et al, 2014). Regression to the mean cannot, be ruled out here as the sample was selected from the “known big eaters” of the donuts. According to Edmonds and Kennedy (2012), the observed changes could be due to regression to the mean and therefore cannot be ruled out here.
5. e) Testing effects are the conditioning results experienced by repeatedly exposing the subjects to a similar testing procedure (Gast et al, 2014). Testing effects can be ruled out as the subjects were never exposed to a repeated test, but rather, the data were collected from existing records.