Correlations in Health Sciences Methodology

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Assignment: CorrelationsIntroductionFrom the onset, it would be prudent to note that statistics knowledge has been applied to various research fields, namely the health sciences, social sciences, and physical sciences. The current paper seeks to assess the relationship and associations between the variables under investigation. Therefore, the current paper aims at investigating the connection/relationship between the usage of caffeine and headaches. Also, the current paper aims at assessing the association between hospital wait times and patient care. Lastly, this particular paper will also investigate if there is a relationship between antibiotic use and weight gain.MethodologyThis section of the paper aims at providing the procedure of the study. The study employed a quantitative method in analyzing the study's results through summary statistics and inferential statistical analysis. Descriptive statistics aims at describing the study's variables in a meaningful and/or simple way/manner (Rio, Tenthorey, & Ramelet, 2021). The analysis will be done on the primary data on caffeine use, headache, hospital wait times, patient care, antibiotic usage and weight gain. Correlation analysis will be used in testing for statistical significance. A correlational design was used to assess the relationship between the study's variables, use of caffeine, headache, hospital wait times, patient care, antibiotic usage and weight gain (Benton, 2021). Therefore, the current study aims to explore the relationship between caffeine use, headache, hospital wait times, patient care, antibiotic usage and weight gain. In conducting the study's analysis, all the data sets were first entered into Excel, and later imported into SPSS version 20 for further statistical analysis.

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An alpha value of 5% was used to evaluate the significance of the results.Results and SummaryThis part…

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…physical health component, (r=-0.078, p=0.022). It should also be noted that from the outputs provided, the original correlations on the matrix were six correlations. The entry of 1.00 indicates a correlation of a variable by itself; if you run a correlation between one variable and itself, you will get 1.00 (Woo & Kim, 2021). The results show that there was a weak significant negative relationship between the body mass index (BMI) and physical health component subscale (r=-0.134, p

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