Highlights
Subject Learning Outcomes
1. Demonstrate understanding of survey design;
2. Demonstrate understanding of the process for creating composite variables and testing reliability and validity;
3. Report on and interpret statistical analysis.
4. Enter data and use strategies for data cleaning; apply a statistical software package for simple data analysis.
Dr Jones is interested in examining the role of smoking and blood glucose levels on systolic blood pressure. Through a cross-sectional survey conducted at a health promotion fair in 2017 in NSW, she collected self-reported data from participants relating to their
1. Demographics: Gender, Age , Highest Educational Level
2. Clinical history:
a. History of blood pressure
b. History of diabetes
c. History of Smoking
d. Actual Blood Glucose Level (BGL)
e. Actual Blood Pressure level (BP)
Dr Jones’s research assistant entered all data in SPSS for data analyses.
Using the SPSS data file that Dr Jones’s research assistant prepared (provided for Assessment 3), answer the following research questions?
Q1 Are there significant gender differences in BGL?
Q2 Is there a significant relationship between gender and history of BP?
Q3 Is there a significant relationship between age and history of smoking
Q4 Construct a descriptive table (means /frequencies as appropriate) for the eight data items collected.
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