Attractiveness and the Halo Effect - Research Proposal Example

Attractiveness and the Halo Effect al Affiliation: This research was conducted to investigate the implications of initial judgment of individuals with regards to their immediate perceptions of the persons they meet. Facial features form a platform through which persons initially relate to a stranger. In this study, 23 pictures of 23 different individuals were provided to 37 participants (two males and 31 females) and the participants asked to rate the persons whose pictures they were given by using a defined criteria of various personal attributes. I used descriptive and inferential (correlation and one-way ANOVA) analysis of data. Based on correlation results between attractiveness and each of the attributes, the findings provided strong evidence for the halo effect on each of the attributes intelligence, warmth, assuredness, ambition, sexiness, friendliness, modesty, competence, and activeness. ANOVA indicated that the gender of individuals in the pictures was significant in making conclusions on each of the attributes. Furthermore, age correlates with sexiness and competence while each of the attributes intelligence, competence and friendliness correlated with few more attributes. Methodology Participants Thirty seven participants were selected for the experiment – two men and thirty five women all with an average age of 33.48 years. The participants were randomly selected to enhance dependability of the results. Materials In this study, I employed a close-ended questionnaire to collect data from the respondents. Each participant was supposed to fill in accurate data that excluded their personal contacts and address details. This measure was taken to ensure that the data collected could not be compromised at all, and that no responses can later be attributed to the respective participants. Ultimately, participant anonymity was a primary undertaking that I underlined to every participant through the questionnaire, and the purpose of the information collected was communicated in advance to the participants. Design A quantitative approach to analysis was adopted to provide mathematically understandable and replicable results. The choice was advised by the ability of quantitative studies to be replicated, and easy referencing of results. Furthermore, such results have a standard way of inference. For instance, the significance levels of parameters of interest can be deduced by setting tests’ significance levels (like 0.05, 0.01, etc) allowing easier-to-understand and predictable inference benchmarks. This opposes the lack of exact benchmarks for developing inferential benchmarks when using qualitative data/ information analysis. Procedure Every participant was issued with a questionnaire. Inside the questionnaire, each participant was presented with a set of 23 pictures, uniformly arranged for all participants. Respondents were supposed to rate their opinions against each of the pictures based on provided criteria. These included their opinions of the people in the pictures regarding attractiveness, intelligence, warmth, assuredness, ambition, sexiness, happiness, friendliness, protectiveness, modesty, competence, masculinity and activeness. On a subjective scale ranging between 0 and 10, the respondents filled in one option that they considered to fit each of the pictures, with 0 representing a relative lack of the attribute, and 10 representing a relative extremity of the attribute. Statistical Analysis The data were analyzed using the SPSS software. Descriptive data analysis provided the initial outlook of the data, while inferential tests provided deeper understanding of the data. In particular, means and standard deviations were obtained for the descriptive part, while correlation coefficients and F-statistics were obtained from correlation analysis and one-way ANOVA tests respectively. Results On the 11 point scale (ranging between 0 and 10), respondents rated the 23 pictures presented to them. The average attractiveness score for all 23 pictures is 5.39 (stdev = 2.39), 6.22 for intelligence (stdev = 2.02), 5.91 for warmth (stdev = 2.23), 6.05 for assuredness (stdev = 2.23), 6.51 for ambition (stdev = 2.19), 5.00 for sexiness (stdev = 2.70), 5.27 for happiness (stdev = 2.35), 6.02 for friendliness (stdev = 2.25), 6.70 for the overall protectiveness (stdev = 2.57), 5.38 for modesty (stdev = 2.13), 6.29 for competence (stdev = 2.05), 5.62 for masculinity (stdev = 3.38), and 6.04 for activeness (stdev = 2.20). The averages are graphically represented below (Figure 1). Figure 1: Average Scores on Personal Attributions. Further, the pictures were classified as being male or female and the average response scores analyzed. Using this categorization, the average male attractiveness score for all 23 pictures is 4.81 (stdev = 2.45) against females’ 6.02 (stdev = 2.17), males’ 5.99 for intelligence (stdev = 2.14) against females’ 6.47 (stdev = 1.85), males’ 5.46 for warmth (stdev = 2.28) against females’ 6.40 (stdev = 2.07), males’ 5.76 for assuredness (stdev = 2.36) against females’ 6.37 (stdev = 2.03), males’ 6.30 for ambition (stdev = 2.24) against females’ 6.74 (stdv 2.11), males’ 4.44 for sexiness (stdev = 2.95) against females’ 5.61 (stdev = 2.25), males’ 5.15 for happiness (stdev = 2.33) against females’ 5.41 (stdev = 2.38), males’ 5.60 for friendliness (stdev = 2.33) against females’ 6.49 (stdev = 2.07), males’ 6.39 for the overall protectiveness (stdev = 2.50) against females’ 7.04 (stdev = 2.60), males’ 5.40 for modesty (stdev = 2.02) against females’ 5.36 (stdev = 2.24), males’ 6.13 for competence (stdev = 2.07) against females’ 6.48 (2.01), males’ 7.62 for masculinity (stdev = 2.39) against females’ 3.44 (2.92), and males’ 5.96 for activeness (stdev = 2.27) against females’ 6.14 (stdev = 2.11). The graphical representation of these averages is included below (Figure 2). Figure 2: Means of Male and Female Assessment Scores To test whether there exists a halo effect, correlation analysis was run to determine the significance of correlation coefficients. Attractiveness was found to correlate significantly with intelligence (r = 0.52, p < 0.001), warmth (r = 0.47, p < 0.001), assuredness (r = 0.47, p < 0.001), ambitiousness (r = 0.50, p < 0.001), sexiness (r = 0.72, p < 0.001), friendliness (r=0.35, p < 0.001), modesty (r = -0.22, p < 0.001), competence (r = 0.46, p < 0.001), and activeness (r = 0.51, p < 0.001). However, attractiveness does not correlate significantly with happiness, protectiveness, and masculinity. Further, a one-way ANOVA test was run to establish whether the genders of people in the pictures had impact on the responses obtained. Effects of gender of people in the pictures were found for attractiveness (F = 48.34, p < 0.001), intelligence (F = 10.21, p < 0.001), warmth (F = 32.77, p < 0.001), assuredness (F = 13.52, p < 0.001), ambition (F = 7.080, p < 0.0010), sexiness (F = 34.92, p < 0.001), friendliness (F = 28.71, p < 0.001), protectiveness (F = 11.39, p < 0.001), competence (F = 5.20, p = 0.02), and masculinity (F = 438.15, p < 0.001). On evaluating the attributes amongst themselves, the following correlation results were obtained. Table 1: Pearson Correlation Test for Relationships between Individual Attributes ‘Age’ correlates with: ‘Intelligence’ correlates with: ‘Friendly’ correlates with: ‘Competent’ correlates with: ‘Sexy’: r = 0.27 p = 0.00 ‘Competent’: r = 0.12 p = 0.00 ‘Warm’: r = 0.52 p = 0.00 ‘Assured’: r= 0.65 p = 0.00 ‘Ambitious’: r = 0.72 p = 0.00 ‘Sexy’: r = 0.38 p = 0.00 ‘Happy’: r = 0.17 p = 0.00 ‘Friendly’: r = 0.42 p = 0.00 ‘Non-threatening’: r = 0.15 p = 0.00 ‘Non-conceited’: r = -0.14 p = 0.00 ‘Competent’: r = 0.63 p = 0.00 ‘Active’: r = 0.52 p = 0.00 ‘Intelligent’: r = 0.42 p = 0.00 ‘Warm’: r = 0.66 p = 0.00 ‘Assured’: r = 0.52 p = 0.00 ‘Ambitious’: r = 0.48 p = 0.00 ‘Sexy’: r = 0.29 p = 0.00 ‘Happy’: r = 0.34 p = 0.00 ‘Not-threatening’: r = 0.23 p = 0.00 ‘Competent’: r = 0.44 p = 0.00 ‘Active’: r = 0.33 p = 0.00 ‘Warm’: r = 0.55 p = 0.00 ‘Assured’: r = 0.64 p = 0.00 ‘Ambitious’: r = 0.66 p = 0.00 ‘Sexy’: r = 0.36 p = 0.00 ‘Happy’: r = 0.12 p = 0.00 ‘Friendly’: r = 0.44 p = 0.00 ‘Non-conceited’: r = -0.25 p = 0.00 ‘Active’: r = 0.59 p = 0.00 Discussion The results obtained in this research have adequately addressed the anticipated answers to research questions. The research provides evidence of the halo effect in individuals’ decisions about the attributes of people they meet. In this analysis, only happiness, protectiveness, and masculinity did not appear to have significant correlations with the overall attribute – attractiveness. The gender of the individual is a strong basis for evaluating their attributes, and this was evident through the responses of participants in this study. In fact, the ANOVA results indicated this based on the significance levels of all the F-ratios for all attributes. Further evidence provides that age is a significant determinant of sexiness and competence. Moreover, intelligence was positively correlated with warmth, assuredness, ambition, sexiness, happiness, friendliness, protectionism, competence and activeness. Friendliness correlated with intelligence, warmth, ambition, assuredness, happiness, protectionism, competence and activeness. Competence was significantly correlated with warmth, assuredness, ambition, sexiness, happiness, friendliness, modesty and activeness. Notably, modesty was negatively correlated with competence, implying that the higher the level of modesty, the lower the level of competence as per the assessments of the respondents in this survey. This could imply that less modest-looking individuals are often considered to be more competent than the more modest-looking ones. A similar observation was also made regarding the relationship between modesty and intelligence. In this case, the higher the level of modesty as per the evaluator’s assessment, the lower the intelligence associated with the individual. These findings are key to forming a basis for further research on the subject. These results partly contradict the findings of Anderson et al. (2001), which indicated that attractiveness is independent of similar attributes as used in this research. References Anderson, C., John, O. 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