Explain how statistical choices in analysis link directly to the research study design that generated the data, and the type of data,

statistics

Description

Objectives This assessment addresses Unit Learning Outcomes 1, 2, 3 & 4: 

• Explain how statistical choices in analysis link directly to the research study design that generated the data, and the type of data, 

• Explain the rationale behind hypothesis testing, and the concept of Type I and II errors, 

• Differentiate the most appropriate descriptive and inferential statistics to use for common types of health data, 

• Analyse health data using a statistical software package, and interpret the results. Task The outbreak of COVID-19 is now widespread across the world and has resulted in a large number of infections and serious health outcomes. The outbreak has infected more than 9,000 people in South Korea to date and their public health response has been praised for quickly reducing the number of infections and casualties. Your task is to answer a set of research questions using current data from the Korean Center for Disease Control & Prevention (sent by e-mail). This data was obtained at a particular point in time (cross-sectional) from cases reported and contains a variety of clinical and epidemiological data. Details of the data set and the variables are provided below. Description of variables Table 1. Coding manual for variables in dataset Name of Variable Variable Description Variable Values patient_id Unique patient identification number Numeric value; NA = missing global_num Cumulative number of case Numeric value from 1 to 10000; NA = missing sex Gender of patient 1 = Male; 2 = Female; NA = missing birth_year Year of birth Numeric value from 1951 to 2020; NA = missing country Country of contact China, France, Korea, etc. NA = missing province Province of South Korea Busan, Seoul, Gang-do, etc; NA = missing (provinces represented will depend on dataset) city City in South Korea Andong-si, Ansan-si, etc; NA = missing disease Pre-exisiting disease identified TRUE/FALSE; NA = missing infection_case Source of infection Overseas inflow, contact with patient, etc; NA = missing infection_order Order of infection Numeric value from 1 to 6; NA = missing infected_by Patient id if source known Numeric value; NA = missing contact_number Number of possible contacts Numeric value from 1 to 1160; NA = missing symptom_onset_ date Date of symptom onset Date; NA = missing confirmed_date Date of positive test for Covid-19 if known Date; NA = missing released_date Date of release from isolation or hospital Date; NA = missing deceased_date Date of death Date; NA = missing state Current status of Covid-19 patient 1 = Isolated, 2 = Released, 3 = Deceased; NA = missing days_rel_conf Number of days from confirmed test to release Numeric value from 1 to 30; NA = missing days_death_conf Number of days from confirmed test to death Numeric value from 1 to 30; NA = missing gender_deaths Gender of patients deceased 1 = Male; 2 = Female; NA = missing A subset of the original dataset (which is unique to you) has been sent by e-mail and you will need to use this version for the Assignment. In your analytical report you are required to answer the following research questions: Answer all of the questions (Q1, 2, 3 & 4): Q1: Is there an association between deaths and gender? (Note: you will need to transform the current status of the Covid-19 patient to be in one of two groups (alive or deceased)). Q2: Is there a difference in age between males and females for those patients deceased? At the end of your summary, critically reflect on how these results provide important information to answer Question 1. (Note: you will need to create a new variable for age which is the difference between the year 2020 and the patients birth year. As the sample size for this analysis is small you can use a threshold of 20% to assess normality. You can also use a significance level of 0.10 and 90% confidence level for the statistical results). Q3: Are there differences in the number of days from confirmed test to release for the provinces identified in your data? Q4: Are age and global number (cumulative number of case) significant predictors of the number of days from confirmed test to release? Firstly describe the relationships between each of the independent and dependent variables, and then identify which of the variables explain the largest amount of variation in number of days from confirmed test to release. If researchers are mostly interested in the association between global number and number of days from confirmed test to release, why is the effect of age being examined (provide details relevant to your data)? (Note: use the new variable age you created for Question 2) For each research question (Q1 to 4) you are required to fully detail an analytical plan, similar to that used in the PUB561 Activity Workbook, Week 5 (page 6 & 7). Please use the marking guide on page 6 to guide the extent of the analysis and answers presented for each question. This should include, at a minimum, the following: 1. State the question 2. Develop and clearly articulate an analysis plan that will allow you to answer the question 3. Implement the analysis plan using Jamovi and report all relevant output. If you need to modify or create new variables to implement the plan then you should describe these new / modified variables and how they were calculated. 4. Interpret the results of the analysis 5. Write a summary paragraph describing the question, the data and the results. Graphics should be incorporated if relevant. 6. Tables and figures in the report should be professionally presented with clear numbering, titles and appropriate referencing in the written sections of the report. e.g Table 1.1 shows the results from a … test examining the association between … Formatting and word limits Your report should contain a title page clearly identifying the unit code, your name and student number. You should also indicate the word count for each section of your report as outlined below and the file name and number of the dataset you used. Failure to do so will result in the assignment not being marked. Each research question should be treated as a separate section in your report and it is expected that you will use appropriate headings within each section. You are not required to provide a formal introduction, search any literature or provide references in your analytical report. The report must: 1) use 12 pt font, 2) have minimum of 1.5 line spacing, and 3) have page margins no smaller than 2cm. It is expected the report will be well written using professional language and be free from grammatical and spelling errors. The written sections of the report should be no longer than 4,000 words excluding the analysis plans, section headings and tables/figures. The valid word count for each question should be stated on the title page of the report. Submission Your assignment MUST be submitted to TURNITIN in the Assessment 2 section of Blackboard. The submission deadline for Question 1 is 11:59pm Sunday 3 rd May 2020 (end of Week 8). Questions 2, 3 & 4 are due 11:59pm Sunday 7 th June 2019. PLEASE NOTE: All requests for extensions must be submitted prior to the due date using the QUT online application (http://external-apps.qut.edu.au/studentservices/concession/ ). Assessment submitted after the due date without an approved extension will not be marked and will receive a grade of 1 or 0%. Please read the instructions for an extension carefully. Marking criteria The analytical report will be marked out of a total of 270 marks according to the criteria on page 6 (last page). Please ensure you review the criteria prior to submitting your assessment. Feedback Feedback will be provided via the criteria marking sheet and written comments on the assessment. Marking criteria Element Max. marks Question 1 (50) 

• Clear & comprehensive analytical plan to answer question that is technically correct including scientific hypothesis, statistical test & assumptions 10 

• Clearly documented evidence that all test assumptions have been tested for validity 10 

• Concise & accurate written summary describing the data 10 

• Comprehensive and correct interpretation and reporting of statistical results 20 Question 2 (60) 

• Clear & comprehensive analytical plan to answer question that is technically correct including scientific hypothesis, statistical test & assumptions 10 

• Clearly documented evidence that all test assumptions have been tested for validity (& revision of analysis if required) 10 

• Concise & accurate written summary describing the data 

• Comprehensive and correct interpretation and reporting of statistical results 20 20 Question 3 (55) 

• Clear & comprehensive analytical plan to answer question that is technically correct including scientific hypothesis, statistical test & assumptions 10 

• Clearly documented evidence that all test assumptions have been tested for validity (& revision of analysis if required) 15 

• Concise & accurate written summary describing the data 

• Comprehensive and correct interpretation and reporting of statistical results 10 20 Question 4 (85) 

• Clear & comprehensive analytical plan to answer question that is technically correct including scientific hypothesis, statistical test & assumptions 20 

• Clear description of univariate & bivariate analysis undertaken 20 

• Clearly documented evidence that all test assumptions have been tested for validity, and test all relevant correlations, describe significant single linear relationships with regression and multiple regression. 30 

• Concise & accurate written summary describing the data 15 Overall Report Overall Report 

• Written report contains all of the required information and adheres to formatting requirements including maximum prescribed length 10 

• Written report uses professional language to clearly articulate meaning with minimal typographic and grammatical errors 10 TOTAL This will be converted to a final mark of 50 270

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