From the Subject Outline:
Assessment task 2: Data in the World: A Data Journey
Intent: This task requires you to analyze data to tell a story that is of personal or professional interest to you. You will apply the statistical and communication skills developed in the class sessions to the dataset, to tell a story about that data.
The purpose of this activity is to give you experience in why and how to find data, how to analyze collected data and how to use the data to tell a story. You should draw conclusions based on analysis of your data.
We will provide examples of data stories, and you may find additional authentic examples at the subject’s Diigo site: https://groups.diigo.com/group/uts-aei/content/tag/data-story This task contributes to the development of Graduate Attributes 1, 2, 3 and 6.
Objective(s): This assessment task addresses subject learning objective(s): 1, 2, 3 and 4.
Type: Project. Group work: Individual Weight: 30%
Task: You will find data and analyze it to tell a story.
You need a short introduction to your data story, including the story of how you collected or located your data. There are some limitations on the type of data to be used, and you need to have your tutor's approval for your choice of dataset.
You should also research and consider external/ independent sources of information on the same theme as your data (e.g., news reports or journal articles). You should then compare and contrast your data, with the external/ independent information.
You will submit a written report which will be assessed (described below). You will also engage in formative activities. These will be assessed by your tutor and contribute to the final mark. (10 marks in total). You need to finish all Checkpoint work on a ‘practice dataset’ assigned by tutor in tutorial time on 29th March.
Submission: Written report. Your report will include:
• A cover sheet (see last page of this Guide), including a title which clearly shows what the story is about.
• An introduction to your data story.
• Graphical illustrations that you have made yourself, showing the main statistical features of the data.
• The appropriate use of descriptive statistics to summarize the data.
• A written analysis of your research on external/independent sources of information.
• Conclusions and mention of any limitations.
You will also submit separately your Excel file with data, calculations and graphs.
FOR STUDENTS IN 36200
Suggested Length: Written report of about 1200 words (excluding appendices and cover sheet) Due: Friday 16 April 2021
FOR STUDENTS IN 36201
Suggested Length: Written report of about 1600 words (excluding appendices and cover sheet)
Due: Friday 16 April 2021
PLANNING AND IN-CLASS FORMATIVE ASSESSMENT TASKS:
Find your data, get it approved, begin preliminary analysis: You need at least 40 rows of data, with at least two quantitative variables (numbers) and at least one qualitative variable
(categories). You may need more than one set of data to achieve this. Start analysing the data. If you cannot find suitable categorical data, check that you have data appropriate for a pie chart or divided bar chart. Online or Face to Face, latest by Thursday 31st March 2021. Submit your ‘chosen’ dataset online when you are ready. Your tutor will discuss your choice with you if necessary, then approve and record the topic of your data. Please note the help available in MSSC (Maths &
Science Study Centre.)
Work on the data set you have been approved for:
Think about the kind of data story you are going to write. What additional sources have you found? How much experience did you gain by the above activities? Perform all summaries, calculations, make graphs and charts on your chosen dataset. Analyse and interpret. Check limitations of your dataset.
SUBMIT ONLINE YOUR FINISHED ASSIGNMENT Your Excel spreadsheet, AND your written report. Use the appropriate submission links online.
LATE ASSIGNMENTS LOSE 10% PER DAY LATE
Your submission is automatically date stamped. If the date is 17th April 2021, you lose 10%, if 18th April 2021 you lose 20% and so on. If you need an extension, email USHA with a medical certificate. Extensions of longer than a week require an application for Special Consideration.
https://www.uts.edu.au/current-students/managingyour-course/classes-and-assessment/specialcircumstances/special
IN-CLASS activity: Checkpoint of AT2: Practice analysis on practice datasets (given by tutor in tutorial) in
tutorial time on 29th March. This is worth up to 10 marks of the assignment total (30).
PLEASE DOUBLECHECK WITH YOUR TUTOR IF THEY HAVE ORGANISED A SESSION ON ZOOM OR MS TEAMS on that day to run the CHECKPOINT activity. IT IS YOUR RESPONSIBILITY TO BE PRESENT IN THE TUTORIAL CLASS ON TIME, BY CHECKING AND ACCESSING THE CORRECT LINK TO YOUR ONLINE TUTORIAL.
Your online tutorial class WILL BE RANDOMLY SPLIT into smaller groups by your tutor. A 'practice dataset' will be given to each group. Everyone in the group must contribute to the work (make statistical summaries, descriptive statistics, make charts and graphs, write analysis), during the tutorial hour and then submit the excel file to CANVAS.
Everyone in the group is awarded the same mark. The group needs to assign a member to submit the completed file on CANVAS. (You will receive a mark ONLY if you participate in the full length of the CHECKPOINT work during tutorial on 29th March.) You should expect to do this Checkpoint work on the ‘practice data set’ with other students – tutors will be on hand to answer questions but are not leading the work. Tutor will collect attendance at an appropriate time during the hour. If you miss the tutorial, you must apply to get 'special consideration' from the Student services.
Your 'Answer Excel file' must be submitted by 12.00 pm (however a grace time of extra 15 min is given, in case of any tech issues) on Monday 29th March. Your tutor will record YOUR GROUP mark afterwards. Evening tutorial groups will run in a similar manner and their CANVAS submissions are due by 7.15pm on the same day.
TWO ATTEMPTS ARE GIVEN TO SUBMIT ANSWER EXCEL FILE on CANVAS. This may help, if someone submits an incorrect file in the first attempt. (No submission means NO MARKS. Emailed files will not be considered.) Marking rubric (for your work on Practice Dataset in TUTORIAL):
• 1 mark for descriptive statistics for a quantitative variable
• 1 mark for five-number summary of a quantitative variable
• 1 mark for a histogram or column chart or time series chart of a quantitative variable • 1 mark for a box plot of a quantitative variable
• 1 mark for a suitable divided bar chart or pie chart or other suitable type
• 1 mark for suitable side by side box plots, or clustered column graphs to show comparisons.
• 1 mark for a suitable scatter plot, line of best fit, r^2 and a correct calculation of correlation coefficient
• 3 marks for writing analysis of the above (this can be done in a cell in Excel file or as a cell comment). For the best mark, we expect academic writing style, interpretation of what the charts are telling, what limitations could be present in the dataset and what can be an interpretation of the above correlation.)
LIMITATIONS AND PROHIBITIONS FOR YOUR CHOICE OF DATASET
This is an INDIVIDUAL and ORIGINAL assignment. Your tutor will ensure that your choice is not the same as others in your tutorial group, and we will be alert for similarities across TUTORIAL groups.
We encourage you to respect academic integrity, which in this case means writing an original assignment yourself, not drawing on the work of students who have already completed this subject.
Type 1
Choose a country (or an Australian State or Australian city) and then a topic in that country or compare two countries (states or cities).
Topics for
State, if AUSTRALIA)
change, Profes
Medical Association,
CFA Institute Clean-up
activities, 2021 are limited to these ideas if
choosing the Country by country (State by option:
, Telehealth, Blood banks,
, Tree change/ Sea
Waterways, Heritage related
sional accrediting bodies (e.g., Royal
Surgeons, Australian
Engineers Australia, CPA,
….), Agriculture, Pet animals,
Australia day, World Music day ountaineering. These topics are
frequently
learning, Work from home, gap, Mobile phones, transparency indices, Air pol Distribution of income,
overuse, influence Climate Change.
Gambling, Australia day prohibited as they have been used
Online Smart cities, Gender pay corruption indices, corporate lution, Recycling, Tourism, Food and Beverage industries,
e.g.,
of social media, Crime statistics, , Composition of
, US elections.
Vocational education
Indigenous perspectives
Nature,
Australasian College of
, etc
M in recent semesters:
All related to COVID, ANY vaccine (related),
Single use plastics, Extra tax on sugar, Social media
Death of democracy
households, Remittances (Guest workers in one country sending money back to their home country),
Type 2
United Nations, its major wings and activities around the world
Type 3
Sports related, Ancient art forms, Musical instruments.
They may be located in the same city, or not! Tell a data story of contrasts.
Type 4
If you think that your chosen data do not fit into any of the above types (and not something related to ‘prohibited types’), please consult your tutor.
You must get approval (for your dataset) by due date of 31st March.
Please note that it is recommended that datasets need data in last 1-2 years.
How will this task be marked?
Written report
The markers will read your written project report online and will choose which category fits for each of the criteria for this task. The criteria are also on the Subject Outline and are repeated here with a table to show you how the markers will decide your mark for each of the criteria. The criteria will be weighted as indicated.
Markers – first check that the ‘dataset’ is the approved one as recorded. If not, do not mark the assignment.
Criterion 1: Has applied appropriate methods to collate original and external data. Weight 3/20.
High Distinction Distinction Credit Pass Fail
Has located or created a sufficient quantity of data (see Pass cell), from a variety of sources in order to tell a convincing data story, including the story of how you located or collected the data. The data are provided in a spreadsheet submitted separately.
The way the data are presented shows care and thought, for example labelling and numbering of tables.
The location and presentation of the data shows considerable imagination and innovation, and critical thinking.
A variety of sources has been used.
Has located or created a sufficient quantity of data in order to tell a convincing data story, (see Pass cell), including the story of how you located or collected the data. The data are provided in a spreadsheet submitted separately.
The way the data are presented shows care and thought, for example labelling and numbering of tables.
The location and presentation of the data shows considerable imagination and innovation.
More than one source has been used.
Has located or created a sufficient quantity of data in order to tell a convincing data story, (see Pass cell), including the story of how you located or collected the data. The data are provided in a spreadsheet submitted separately.
The way the data are presented shows care and thought, for example labelling and numbering of tables.
Has located or created a sufficient quantity of data in order to tell a data story, including the story of how you located or collected the data. The data are provided in a spreadsheet submitted separately.
At least forty rows of data, and at least three variables should be recorded. (At least two quantitative variables and at least one qualitative variable). This may be in more than one set.
(We need to be able to see your data and follow in Excel
how you made your graphs etc.)
The source of the data is clearly referenced and can be checked.
If the source of the data is questionable, the marker will not continue marking and you will fail the entire assignment.
If you have fewer than forty rows of data with at least three variables you will score less than half the marks for this criterion.
Criterion 2: Has applied key concepts in statistics and probability to draw conclusions from analysis. Weight 4/20.
High Distinction Distinction Credit Pass Fail
All of the sentences in the Distinction cell apply, and in addition:
Evidence is provided of individual learning beyond the techniques presented in class, so that it is clear that the student has learnt a statistical concept or concepts that they did not know before.
All of the sentences in the Credit cell apply, and in addition:
The conclusions follow from the data and show considerable insight based on an understanding of probability. (Has appropriately used statements like “according to these data it is likely that…”)
Calculations of summary statistics are shown. This could be done within Excel but needs to be seen.
Has used appropriate summary statistics to summarise the data and to draw conclusions. The conclusions follow from the data and are clearly described.
Calculations of summary statistics are shown. This could be done within Excel but needs to be seen. Summary statistics includes the five-number summary: the mean, the mode, and the standard deviation. Has used appropriate summary statistics to summarise the data and to draw conclusions, which are mostly appropriate.
Calculations of summary statistics are inadequately presented, with few conclusions drawn from the data.
Summary statistics includes the five-number summary: and descriptive statistics (the mean, median, mode, range and the standard deviation).
If there are no tables of statistics in the word document, you will score a zero for this criterion.
Criterion 3: Has created graphical and visual representations of data, which are described and analysed. The graphs are inserted into the Word Document and are described near the place where they appear. (Not grouped at the end in an appendix). Weight 4/20.
High Distinction Distinction Credit Pass Fail
Has created appropriately at least two kinds of charts, pie charts, column graphs, line graphs, time series etc.
AND
Has created appropriately at least three kinds of visual display of comparison (e.g., At least three of: scatter plot to investigate relationships between two sets of quantitative data; side-byside box plots, clustered column graphs, two or more line graphs on same axes to show comparisons
Clearly written and correct description and quantitative analysis, including discussion of trends, correlation, and outliers (if any).
Has created appropriately at least two kinds of chart, pie chart, column graph, line graph, time series etc.
AND
Has created appropriately at least two kinds of visual display of comparison (e.g., At least two of: scatter plot to investigate relationships between two sets of quantitative data; side-by-side box plots, clustered column graphs, two or more line graphs on same axes to show comparisons.)
Clearly written and correct description and quantitative analysis, including a discussion of trends, and outliers (if any).
Has created appropriately at least two kinds of chart for a single variable: pie chart, column graph, line graph, time series, etc.
AND
Has created appropriately at least two kinds of visual display of comparison (e.g., At least two of: scatter plot to investigate relationships between two sets of quantitative data; side-by-side box plots, clustered column graphs, two or more line graphs on same axes to show comparisons.)
Written description and analysis are generally clear.
Has created appropriately at least one kind of chart for a single variable: pie chart, column graph, line graph, time series etc.
AND
Has created appropriately at least one kind of visual display of comparison (e.g., Scatter plot to investigate relationships between two sets of quantitative data; side-by-side box plots, clustered column graphs, two line graphs on same axes to show comparisons.)
There may be some errors or missing labels in graphs, or choice of kind of graph is incorrect. Written description may be inadequate.
Has made some graphs but not sufficient as described in the “Pass” cell.
If you have not created any graphs of your own, using the data collected, you will score a zero for this criterion.
Criterion 4: Has demonstrated effective communication skills appropriate to the written genre. Weight 4/20.
High Distinction Distinction Credit Pass Fail
Has told a convincing data story. The story is clearly structured and is based on the statistical evidence.
The links are clear and are effectively established.
The writing is of a very high quality, presenting a clear argument.
Has told a convincing data story. The story is clearly structured and is based on the statistical evidence.
The links are clear and are effectively established, but some irrelevant material may be included.
The writing is clear but the structure could be improved.
Has told a convincing data story. The story is clearly structured and links to the statistical evidence, but some links are not clear and irrelevant material may be included in a way that detracts from the story.
Minor errors of grammar and syntax did not detract from the story.
Has told a data story but the story is poorly structured and links to the statistical evidence are not clear.
Minor errors of grammar and syntax detract from the story.
Has not told a convincing data story. The story is poorly structured and does not link adequately to the statistical evidence.
Major errors of grammar and syntax make the story unclear.
Criterion 5: Has critiqued findings and analysis, drawing on relevant external information to demonstrate the quantitative literacy capacities of informed and ethically aware citizens. (a) (External sources) Weight 3/20.
High Distinction Distinction Credit Pass Fail
Compares the story to other sources, with references, making judgements that demonstrate considerable insight. Compares the story to other sources, with references, making some sound judgements. Makes an attempt to compare the story to other sources, with references.
Makes an attempt to compare the story to other sources.
If you make no attempt to compare the story to other sources, you will score a zero on this criterion.
Criterion 5: Has critiqued findings and analysis, drawing on relevant external information to demonstrate the quantitative literacy capacities of informed and ethically aware citizens. (b) (Limitations) Weight 2/20.
High Distinction Distinction Credit Pass Fail
Demonstrates a clear and appropriate awareness of the limitations of the data story they have written. Reasons for statements about this in their conclusion are well expressed and demonstrate a deep level of analysis.
Demonstrates a clear and appropriate awareness of the limitations of the data story they have written, giving reasons for statements about this in their conclusion.
Demonstrates a sound awareness of the limitations of the data story they have written.
Demonstrates some awareness of the limitations of the data story they have written.
If you do not demonstrate an awareness of the limitations of the data story you have written, you will score a zero for this criterion.
Please copy this table and make it your cover sheet for your Word document. (Do not submit a pdf).
SUBJECT NUMBER & NAME 36200 OR 36201 (Delete one)
Arguments, Evidence, and Intuition
NAME OF STUDENT
STUDENT ID NUMBER
Tutor’s name
ASSIGNMENT TITLE (Maximum 10 words)
(Your personal title, not just “AT2”)
ASSESSMENT ITEM NUMBER/ TITLE AT2: Data in the world: A Data Journey
Be sure to save the word document and spreadsheet separately with filenames that identify you clearly.
Preferred is last name and student number and AT2, like this (e.g., SMITH12344321AT2).
Check that you have included in your Word document.
• The link to your data source (if you have searched your own)
• Tables of statistics – the five-number summary and the descriptive statistics, with comments.
• A selection of your graphs and charts/data visualizations that you have made to illustrate your data story.