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## Statistics

Assessment - Analytical Report

Objectives - This assessment addresses Unit Learning Outcomes:

• Discriminate the most appropriate descriptive and inferential statistics to use in a given health context,
• Analyse health data using statistical software and interrogate the test assumptions, and
• Interpret and communicate the results of computer-generated statistical analyses.

Your task is to write the statistical methods and results sections of a hypothetical manuscript that focuses on casual serum glucose level in a cohort of individuals who were part of the Framingham Heart Study which commenced in 1948 in the community of Framingham, Massachusetts USA. The SPSS data set you are required to analyse was emailed to your QUT student email address on 10th September. If you did not receive this email you should notify the unit coordinator immediately. The data coding manual for the data set is provided at the end of this document.

Your analysis and reporting of results should encompass all of the following tasks/questions.

1. Describe the characteristics of the people included in the sample at the baseline examination.

2. Describe and test the bivariate relationships between casual serum glucose at the baseline examination and age, body mass index (BMI), education and use of blood pressure medication at the time of the baseline examination.

3. Describe the people who had casual serum glucose >150 mg/dL at the baseline examination and compare them to people who had ≤150 mg/dL casual serum glucose at the baseline examination in terms of age, BMI, whether they were cigarette smokers at baseline examination and whether they were taking blood pressure medication at the time of the baseline examination.

4. Considering only individuals with casual serum glucose level at baseline less than or equal to 150 mg/dL, which of these variables (age, BMI, smoking status and whether they were taking blood pressure medication) measured at baseline are significantly associated with casual serum glucose level at baseline in a multivariable analysis? Describe their relationship with casual serum glucose level, including which continuous variable explains the most variation in casual serum glucose level. Report the 'minimum model' obtained.

5. Did the average casual serum glucose level of participants change significantly between the baseline examination and the follow-up examination? Did the proportion of the sample with casual serum glucose level >150 mg/dL change significantly between baseline and follow-up examination?

The report structure -

Your report should contain two sections; statistical methods and results. You are permitted to use subheadings within the results section. You are not required to research the background to the data, or the relevance of the results to the field. You are also not required to reference the data or statistical methods used.

The articles available on QUT Readings under the heading "Papers for Orientation Week exercise" provide examples of how statistical methods and results are reported in manuscripts. It is recommended you review some of these articles so you are familiar with options for how to present your results.

Your report should be written in clear English, using sentences and proper grammar. The report can contain tables and graphs, however copying SPSS output is not permitted. Only the graphs from SPSS can be included. Self-generated tables containing relevant information are acceptable but copy-paste tables from SPSS are not appropriate. Remember that your task is to interpret the results which means the reader should not need to see all the details of the output you obtained. Also remember to include both descriptive and inferential statistics. The reader should be able to understand the analysis you conducted and the assumptions you considered from reading the statistical methods section. The report must not include analytical plans, and appendices will not be considered when grading reports.

Attachment:- Assignment Files.rar

Applied Statistics, Statistics

• Category:- Applied Statistics
• Reference No.:- M93130785

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