This assessment addresses the following learning outcome: a) Understand key concepts in statistics and the way in which both descriptive and inferential statistics are used to measure, describe and predict health and illness and the effects of interventions b) Investigate survey design in order to collect valid and reliable data and sampling techniques to minimise bias c) Evaluate the application of parametric and nonparametric statistical tests, and how to control for confounding variables d) Understand when to use different types of inferential statistics, including chi-square analysis, t-tests, analysis of variance (ANOVA), correlation and linear regression, and how to interpret the results of these analyses e) Apply key terms and concepts of statistics, including; sampling, hypothesis testing, validity and reliability, statistical significance and effect size f) Interpret the results of commonly used statistical tests presented in published literature
Microsoft Word - STAT6000 Supplementary Assessment Brief.docx SubjectCode_Assessment_#_Brief_AssesmentType_Module Due# Page 1 of 2 Context: This assessment aims to consolidate student’s knowledge of the topics covered in Modules 1-6. By completing the exercise, students will be able to demonstrate their understanding of the key concepts discussed in Statistics for Public Health. Instructions: • A maximum of 80 marks is set for this supplementary assessment and you need to get at least 40 marks to receive a SUPPLEMENTARY PASS grade. • Some questions will require basic computations with a calculator, excel or pen and paper. You will need to show how you calculated your answers (i.e., show the solution). • For questions that ask you to explain how/why you selected a particular answer, you need to respond using no more than 50 words. SUPPLEMENTARY ASSESSMENT BRIEF Subject Code and Title STAT6000 Statistics for Public Health Assessment Supplementary Assessment Individual/Group Individual Length Maximum of 800 words Learning Outcomes This assessment addresses the following learning outcome: a) Understand key concepts in statistics and the way in which both descriptive and inferential statistics are used to measure, describe and predict health and illness and the effects of interventions b) Investigate survey design in order to collect valid and reliable data and sampling techniques to minimise bias c) Evaluate the application of parametric and nonparametric statistical tests, and how to control for confounding variables d) Understand when to use different types of inferential statistics, including chi-square analysis, t-tests, analysis of variance (ANOVA), correlation and linear regression, and how to interpret the results of these analyses e) Apply key terms and concepts of statistics, including; sampling, hypothesis testing, validity and reliability, statistical significance and effect size f) Interpret the results of commonly used statistical tests presented in published literature Submission By 31 May 2021, 11:55pm AEST, Monday Weighting Pass/Fail Total Marks 80 marks SubjectCode_Assessment_#_Brief_AssesmentType_Module Due# Page 2 of 2 • You need to create a new document and outline your answers as it is numbered in the Supplementary Assessment document. Please submit your work to alex.gavino@torrens.edu.au on or before the due date. Microsoft Word - STAT6000 Supplementary Assessment.docx STAT6000 Supplementary Assessment 1. The data in the following table shows the number of fast-food burgers consumed per week in a sample of Australian teenagers. Subject ID Number of Fast-Food Burgers per Week 1 2 2 2 3 5 4 0 5 14 6 4 7 3 8 2 Reporting to one decimal place, calculate the following: (a) Mean = ___________ (2 points) Explain how you calculated the mean. Show your solution. (2 points) (b) Median = ___________ (2 points) Explain how you determined the median. (2 points) (c) Mode = ___________ (2 points) Explain how you identified the mode. (2 points) (d) Range = ___________ (2 points) Explain how the range is determined. (2 points) 2. The data in the table below shows infant birth weights and mortality among infants in New York City in 1974. The objective of this study is to investigate whether infant mortality is related to birth weight. Risk factor Outcome Total Dead Alive Low birth weight 618 4597 5215 Normal birth weight 422 67093 67515 Total 1040 71690 72730 (a) Describe the relationship between the two variables: birth weight and survival. Which is the dependent variable? Which is the independent variable? (5 points) (b) What is the proportion of deaths amongst low birthweight babies? Show how you calculated this. (5 points) (c) What is the proportion of deaths amongst normal birthweight babies? Show how you calculated this. (5 points) (d) What is the appropriate statistical test to compare the proportion of deaths among low birth weight babies to the proportion of deaths among normal birth weight babies? Explain why you selected that test. (5 points) 3. A study was undertaken to investigate attitudes of adults in Australia to alcohol use. An electronic copy of the White Pages phone book for the Melbourne area was used as the sampling frame, and a random number generator was used to select which numbers to call. Out of 4 million adults living in Melbourne, a total of 6,453 eligible adults were contacted and invited to take part in September 2010. Of these 4,772 completed the telephone interview. (a) What group constitutes the population in this study? (1 point) (b) What is the sample size in this study? (2 points) (c) What is the sampling fraction? Show how you calculated the sampling fraction. (3 points) (d) What is the response rate? Show how you calculated the response rate. (3 points) 4. You want to find out whether there is an association between coeliac disease and anxiety amongst South Australian women aged between 18-45. Both variables are coded as yes/no variables. What is the best test to use to explore this relationship? Explain why you selected that test. (5 points) 5. You want to determine whether there is an association between the number of years that the participants have lived with coeliac disease and their score from an anxiety questionnaire. Participants wrote the number of years lived with the disease as a whole number, and the anxiety score is the sum of their responses to the questions, so both variables are scale variables. Their distribution is normal. What is the best test to use to explore this relationship? Explain why you selected that test. (5 points) 6. You want to determine whether the anxiety scores are different for men and women. The anxiety scores are continuous variables calculated from the sum of their responses to the questions, and ‘gender’ is a categorical variable (male/female). The distribution of the anxiety scores is normal. What is the best test to use to explore this relationship? Explain why you selected that test. (5 points) 7. The result of a statistical test produced a significance value of p=0.02. What does this p value tell you? (5 points) 8. The result of a statistical analysis of odds ratio data produced a confidence interval ranging from 0.03 – 2.39. What does the confidence interval tell you in terms of the odds ratio? Will you reject or accept the null hypothesis? (5 points) 9. You are analysing a data set for atrial fibrillation (AF). The outcomes are ‘AF’ and ‘no AF’. The independent variables are ‘blood pressure’, ‘BMI’, and ‘blood glucose’. What is the most appropriate statistical test to measure the relative contribution of the independent variables to the outcomes? Explain why you selected that test. (5 points) 10. We want to see whether an intervention was effective in improving students’ confidence by comparing their scores from time 1 with their score from time 2. What is the correct test to use to explore this? Explain why you selected that test. (5 points)