ASSESSMENT 3 BRIEF
Subject Code and Title STAT6200 Biostatistics
Assessment Data Visualisation, Distribution & Analysis
Individual/Group Individual
Length 250-word (+/- 10%) abstract and 8-10 minute recorded audio presentation of statistical tests as performed on SPSS
Learning Outcomes This assessment addresses the following learning outcomes:
a) Critically apply the theories on key concepts in descriptive and inferential statistics
c) Assess the data and determine the appropriate parametric and non-parametric statistical tests, and how to control for confounding variables
d) Evaluate types of inferential statistics and interpret the results of these analyses using theoretical examples or as presented in published literature
e) Apply key concepts of statistics, including: sampling, hypothesis testing, distribution of data, validity and reliability, statistical significance and effect size
Submission Due Sunday following the end of Module 11 at 11:55pm
AEST/AEDT*
Weighting 30%
Total Marks 100 marks
Instructions:
As part of your Public Health role, you have been asked to perform statistical analysis of a data set from a research project and provide the results of your analysis in abstract form.
This assessment has two parts.
Part 1
Demonstrate your ability to use the Statistical Package for the Social Sciences (SPSS) software to perform statistical analysis of a data set.
From the datasets provided, select ONE of three data sets to download and import the Excel data set into SPSS.
You can view the description of the datasets and download the relevant dataset Excel spreadsheet from the Assessment 3 folder of this subject.
While recording the process using screen capture, execute the following statistical processes in SPSS using the following sequence:
1. Generate a boxplot for group A and group B to check for data outliers and remove any outliers from your subsequent analysis, if present.
2. Create a frequency histogram for group A and group B to check the distribution of the data and decide which parametric or non-parametric test is appropriate to compare the two groups.
3. Use the appropriate normality test to determine the distribution of groups A and B, and use the correct inferential statistical test to compare the two groups. Decide if there is a significant difference in the measure of central tendency for the two groups.
Part 2
Write a 250-word abstract to report the findings of Part 1. This should include:
1. Aim: one or two sentences describing the purpose of the research study; a short background to the study is included with each data set.
2. Methods: describe which statistical methods were applied in SPSS
3. Results: report the key summary statistics and P value using conventions required for formal reporting of statistical results
4. Conclusion: briefly describe the significance of your results
Additional resources:
1. Access to the SPSS platform
2. Screen capture recording can be performed in Windows 10 using Xbox Gamebar (https://www.youtube.com/watch?v=kpZUN-ae4ts) or in Mac Os using Quicktime (https://www.youtube.com/watch?v=prUVS0HF2gU).
Referencing
It is essential that you use appropriate APA style for citing and referencing research. Please see more information on referencing here https://library.torrens.edu.au/academicskills/apa/tool
Submission Instructions
Submit this task via the Assessment link in the main navigation menu in STAT6200 Biostatistics. The Learning Facilitator will provide feedback via the Grade Centre in the LMS portal. Feedback can be viewed in My Grades.
Academic Integrity Declaration
I declare that except where I have referenced, the work I am submitting for this assessment task is my own work. I have read and am aware of Torrens University Australia Academic Integrity Policy and Procedure viewable online at http://www.torrens.edu.au/policies-and-forms
I am aware that I need to keep a copy of all submitted material and their drafts, and I will do so accordingly.
Assessment Rubric
Assessment Attributes Fail
(Yet to achieve minimum standard) 0-49% Pass
(Functional)
50-64% Credit
(Proficient) 65-74% Distinction
(Advanced)
75-84% High Distinction
(Exceptional)
85-100%
Accuracy and quality of descriptive statistical analysis: boxplots in SPSS
20%
Failed to provide the descriptive measures for the data provided: Both boxplots absent or one boxplot absent and one boxplot plotted
incorrectly (with outliers)
Shows limited understanding of descriptive measures and
the statistical analysis is incorrect and wrongly interpreted:
One boxplot absent and one boxplot plotted correctly (no
outliers)
Shows some understanding of the numerical descriptive measures, however there are some mistakes in the statistical analysis and interpretations: Both boxplots plotted incorrectly (with outliers) Shows adequate knowledge of the descriptive measures. A number of minor mistakes in the statistical analysis may be present: One boxplot plotted correctly (no outliers) and one boxplot plotted
incorrectly (with outliers)
Student shows superior knowledge of the descriptive measures with no mistakes: Both boxplots plotted correctly (no outliers)
Accuracy and quality of descriptive statistical analysis: histograms in SPSS
20%
Failed to provide the descriptive measures for the data provided:
Both histograms absent or one histogram absent and one histogram plotted
incorrectly (with outliers)
Shows limited understanding of descriptive measures and
the statistical analysis is incorrect and wrongly interpreted:
One histogram absent and one histogram plotted
correctly (no outliers)
Shows some understanding of the numerical descriptive measures, however there are some mistakes in the statistical analysis and interpretations:
Both histograms plotted incorrectly (with outliers) Shows adequate knowledge of the descriptive measures. A number of minor mistakes in the statistical analysis may be present: One histogram plotted correctly (no outliers) and one histogram plotted
incorrectly (with outliers)
Student shows superior knowledge of the descriptive measures with no mistakes: Both histograms plotted correctly (no outliers)
Application of inferential statistical
methods in SPSS
20%
Demonstrates no understanding of the methods and concepts relevant to the inferential statistical data analysis:
No normality test, wrong data distribution described for both A and B; incorrect Demonstrates little understanding of the methods and concepts relevant to the inferential statistical data analysis:
No normality test, correct data distribution described for A or B; incorrect inferential Demonstrates good knowledge of the methods and concepts relevant to the inferential statistical data analysis: No normality test, correct data distribution described for A or B; Demonstrates correct knowledge of the methods and concepts relevant to the inferential statistical data analysis:
Normality test performed, correct data distribution described for A or B; correct Demonstrates correct and complete knowledge of the methods and concepts relevant to the inferential statistical data analysis: Normality test
Assessment Attributes Fail
(Yet to achieve minimum standard) 0-49% Pass
(Functional)
50-64% Credit
(Proficient) 65-74% Distinction
(Advanced)
75-84% High Distinction
(Exceptional)
85-100%
inferential test used test used
correct inferential test used inferential test used performed, correct data distribution described for both A and B; correct
inferential test used
Effective communication
(Abstract)
20%
Meaning is repeatedly obscured by errors in the communication of ideas, including errors in structure, sequence, spelling, grammar, punctuation and/or the acknowledgment of sources.
Limited or no understanding of the statistical data analysis: All fours sections of the
abstract have errors
Meaning is sometimes difficult to follow.
Information, arguments and evidence are structured and sequenced in a way that is not always clear and logical.
Identifies a proportion of the
understanding of the statistical data analysis: One section of the abstract is reported clearly and accurately and three have errors Meaning is easy to follow. Information, arguments and evidence are structured and sequenced in a way that is clear and logical.
Identifies a majority of the understanding of the statistical data analysis: Two sections of the abstract are reported clearly and accurately and two have errors Engages audience interest. Information, arguments and evidence are structured and sequenced in a way that is clear and persuasive.
Correctly identifies all of the analytical techniques and understanding of the statistical data analysis: Three sections of the abstract are reported clearly and accurately and one has
errors
Engages and sustains audience’s interest. Information, arguments and evidence are insightful, persuasive and expertly presented.
Not only identifies all of the analytical techniques with good understanding of the statistical data analysis:
All fours sections of the abstract are reported
clearly and accurately
Assessment Attributes Fail
(Yet to achieve minimum standard) 0-49% Pass
(Functional)
50-64% Credit
(Proficient) 65-74% Distinction
(Advanced)
75-84% High Distinction
(Exceptional)
85-100%
Effective
Communication
(Presentation/Oral in SPSS)
20%
Difficult to understand for audience, no logical/clear structure, poor flow of ideas, argument lacks supporting evidence.
Specialised language and terminology is rarely or inaccurately employed.
Presentation is sometimes difficult to follow.
Information, arguments and evidence are presented in a way that is not always clear and logical.
Employs some specialised language and terminology with accuracy.
Presentation is easy to follow.
Information, arguments and evidence are well presented, mostly clear flow of ideas and arguments.
Accurately employs specialised language and terminology.
Engages audience interest. Information, arguments and evidence are very well presented; the presentation is logical, clear and wellsupported by evidence.
Accurately employs a wide range of specialised language and terminology.
Engages and sustains audience interest. Expertly presented; the presentation is logical, persuasive, and well- supported by evidence, demonstrating a clear flow of ideas and arguments.
Discerningly selects and precisely employs a wide range of specialised language and terminology.
The following Subject Learning Outcomes are addressed in this assessment
SLO a) Critically apply the theories on key concepts in descriptive and inferential statistics
SLO c) Assess the data and determine the appropriate parametric and non-parametric statistical tests, and how to control for confounding variables
SLO d) Evaluate types of inferential statistics and interpret the results of these analyses using theoretical examples or as presented in published literature
SLO e) Apply key concepts of statistics, including: sampling, hypothesis testing, distribution of data, validity and reliability, statistical significance and effect size