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Assessing non-parametric or t tests - Essay Example

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Name Institute of Affiliation Assessment Date Abstract: The paper focuses on the assessment of non-parametric and t tests of a related article. Keywords: Non-parametric, t tests . ASSESSING NON-PARAMETRIC OR T TESTS In this study, Stark, Chase and DeYoung (2010) have primarily focused on two concepts: first is the health promotion and another is attention demand…
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Assessing non-parametric or t tests
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Download file to see previous pages The Cronbach alpha value of HPLPII was 0.95, which is reliable and valid for study; as HPLPII has been divided into further six subscales which are health responsibility (HR), physical activity (PA), nutrition (NUTR), spiritual growth (SG), interpersonal relations (IPR), and stress management (SM). The Cronbach alpha’ individual subscale values are stated as 0.83 for HR, 0.87 for PA, 0.85 for NUTR, 0.86 for SG, 0.82 for IPR and 0.76 for SM. Second concept of Attentional Demands Survey (ADS) is valid as Cronbach alpha values stood at 0.96. Since ADS was further divided into four subscales as Physical Environmental (PE), Informational (INF), Behavioural (BEH) and Affective (AF). The Cronbach alpha for all four internal subscales was reported as 0.90 for PE, 0.91 for INF, 0.84 for BEH and 0.88 for AF. Considering all the reported statistics of Cronbach Alpha; it can be argued that all variables are valid and reliable for further testing; it should be noted that acceptance of Cronbach Alpha test statistic is 0.8 for previously tested models and 0.7 for newly tested models. After validation, it should be noted that this study is a correlational study so, obviously the next step will be to analyse the correlation between the survey findings of Attentional Demand Survey (ADS) and Health Promoting Lifestyles Profile II. The resulted correlation between ADS and HPLPII was a moderate negative correlation though all the indicators were significant at 5% level of significance as p statistics for all correlation statistics was below 0.05. After open analysis the sample was categorized into age groups. One way ANOVA test was applied to find the significance of age differences and health promotion. The result statistics revealed significant difference of health promotion between two groups of age 65-74 and age 75-84 but the age group 85 to older had no significant difference in health promotion. The One way ANOVA test statistics revealed the significance of age group differences as p stood at 0.027 with the F-test statistics at 3.72. In the parametric dimension of analysis ADS was consider responsive to the nursing facility for which demographic differences such as marital status differences and gender differences were tested for relationship. Marital status differences were not significant and there was no difference in health promotion while testing their marital differences as t-test statistics for ADS was 0.42 and for HPLPII was -0.42, both t-test statistics were below 2. Similarly gender differences for health promotion were also insignificant as t-test statistic for ADS was 0.76 and for HPLPII was -1.42. Besides parametric testing, the study also opted for some non-parametric testing as attentional demands and difficulties by different age groups were specified and the study compiled the survey results and presented it in tables which was categorized in three age groups. These non-parametric analysis helped understanding the qualitative dimension of the study. The article is actually based on the growing healthcare problems among the dwelling elders in USA and examines the barriers to health promotion among them. The elderly population of today is known as the baby boomer generation who have ...Download file to see next pagesRead More
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