HA1011 Applied Quantitative Methods Group Assignment

HA1011 Applied Quantitative Methods
Assessment Details and Submission Guidelines
TrimesterT1 2022
Unit CodeHA1011
Unit TitleApplied Quantitative Methods
Assessment TypeAssessment 2
Assessment TitleGroup Assignment (Min of 2 and maximum of 4 members in a group. Please check the group self-enrollment guide in the assessment folder)
Purpose of the assessment (with ULO Mapping)Students are required to understand the principles and techniques of business research and statistical analysis taught in the course.
Weight40% of the total assessments
Total Marks40
Word limitN/A
Due DateWeek 10 (27th of May 2022)
Submission GuidelinesAll work must be submitted on Blackboard by the due date and a completed Assignment Cover Page.The assignment must be in MS Word format only, with no spacing, 12-pt Arial font and 2 cm margins on all four sides of your page with appropriate section headings and page numbers.Reference sources must be cited in the text of the report and listed appropriately at the end in a reference list using Harvard referencing style.

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HA1011 Applied Quantitative Methods Group Assignment

Assignment Specifications


This assignment aims at assessing students’ understanding of different qualitative and quantitative research

methodologies and techniques. Other purposes are:

  1. Explain how statistical techniques can solve business problems
  2. Identify and evaluate valid statistical techniques in a given scenario to solve business problems
  3. Explain and justify the results of statistical analysis in the context of critical reasoning for a business problem solving
  4. Apply statistical knowledge to summarise data graphically and statistically, either manually or via a computer package
  5. Justify and interpret statistical/analytical scenarios that best fit business solution

Assignment Structure should be as the following:


•          Your assignment must be submitted in WORD format only.

  • When answering questions, wherever required, you should copy/cut and paste the Excel output (e.g., plots, regression output etc.) to show your working/output. Otherwise, you will not receive the allocated marks.

•          You must keep an electronic copy of your submitted assignment to resubmit if the original submission has failed and you are asked to resubmit.

  • Please check your Holmes email before reporting your assignment mark regularly for possible communications due to failure in your submission.
Important Notice: All assignments submitted undergo plagiarism checking; if found to have cheated, all involving submissions would be subject to penalties.

HA1011 Applied Quantitative Methods

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Group Assignment Questions

Adila Group of Companies is a research firm established in Melbourne CBD. They mainly provide their service to real estate investors. Assume your group is the data analytics team on Adila Group of Companies. Based on that assumption, access any of the following websites to prepare a report based on the requirements listed below.

You are required to,

  1. Access rental property details from one of the above online sources, select a specific state (NSW, QLD, SA, TAS. VIC or WA), and prepare a data table with a minimum of 50 observations

Variable required

  1. Weekly rent
    1. Number of bedrooms (minimum of 10 property details in each for houses with 1, 2, 3 and 4 bedrooms)
    1. Number of car space
    1. Number of bathrooms
    1. Date Available
    1. Bond
    1. Hyperlink for the selected rental property

Note: You must use the most recent data, share the details on data sources and are not allowed to use hypothetical data.

  • Perform descriptive statistical analysis and prepare a table with the following descriptive measures for the Weekly rent variable in your data set.

Mean, median, mode, variance, standard deviation, skewness, kurtosis, coefficient of variation.

  • Critically review the descriptive statistics in part (2) and explain the nature of the distribution of those variables.
    • Derive a suitable graph to represent the relationship between weekly rent and other variables in your data set.

(Relationship between weekly rent and no of bedrooms, the relationship between weekly rent and no of car space, the relationship between weekly rent and no of bathrooms)

  • Based on the data set, perform a correlation analysis between Weekly rent, No of bedrooms, No of car space, and No of bathrooms.
    • Comment on the observed trends between variables based on the answer for Q4 and Q5.
    • Based on the data set, perform a simple regression analysis to assess whether no of bedrooms is a determinant of weekly rent and answer the questions below
  1. Derive the simple regression equation and Interpret the meaning of all the coefficients.
    1. Interpret the coefficient of determination.

HA1011 Applied Quantitative Methods

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  • Based on your regression equation in (a), estimate the weekly rent of a house with four bedrooms

Marking criteria

Marking criteriaWeighting
Collection of the data set which meets the given guidelines (Q1)5 marks
Preparation of descriptive statistical table for the weekly rental variable (Q2)4 marks
A critical review of calculated descriptive statistics (Q3)4 marks
Derive Suitable graphs for an analysis of the relationship between variables(Q4)3 marks
Correlation analysis3 marks
Critical review of relationship between variables based on answers in Q4 and Q5. (Q6)3 marks
Deriving simple regression output using excel3 marks
Deriving simple regression equation based on the regression output and interpretation of regression coefficients5 marks
Interpretation of coefficient of determination.4 marks
Use of regression for prediction2 marks
Quality of the report4 marks
TOTAL Weight40 Marks
  Assessment Feedback to the Student: 

HA1011 Applied Quantitative Methods

Marking Rubric

 ExcellentVery GoodGoodQuestionableUnsatisfactory
Collection of data setDemonstration ofDemonstration ofDemonstration ofDemonstration ofDemonstration of poor
which meets the givenoutstanding knowledgevery goodgood knowledgebasic knowledge onknowledge on gathering
guidelineson gathering data fromknowledge onon gathering datagathering data fromdata from online sources.
 online sources.gathering data fromfrom onlineonline sources. 
  online sources.sources.  
Performing descriptive statistical analysis based on manual or excel calculationDemonstration                      of outstanding knowledge on                      descriptive measuresDemonstration                              of very               good knowledge               on descriptiveDemonstration of good knowledge on descriptive measuresDemonstration                           of basic knowledge on descriptive measuresDemonstration of poor knowledge on descriptive measures
Critical review of calculated descriptive statisticsDemonstration                           of outstanding knowledge on use of descriptive measuresDemonstration               of very               good knowledge on use of descriptiveDemonstration of good knowledge on use of descriptive measuresDemonstration                           of basic knowledge on use of descriptive measuresDemonstration of poor knowledge on use of descriptive measures
Deriving suitable graph toDemonstration   ofDemonstration                           ofDemonstration                              ofDemonstration                             ofDemonstration of poor knowledge           on presentation        of data using suitable chart types.
represent the relationshipoutstanding knowledgevery       goodgood knowledge onbasic knowledge on
between variableson presentation of dataknowledge                           onpresentation                              ofpresentation of data
 using               suitable chartpresentation of datadata using suitableusing suitable chart
 types.using presentation ofchart types.types.
  data using suitable  
  chart types.  
Preforming Correlation analysis using excel and critical review of the correlationDemonstration of outstanding knowledge on correlation analysisDemonstration                              of very               good knowledge               on correlation analysisDemonstration of good knowledge on correlation analysisDemonstration of basic knowledge on correlation analysisDemonstration of poor knowledge on correlation analysis
Deriving simple regression equation based on the regression output and interpretation of regression coefficients  Demonstration                           of outstanding knowledge on regression modelDemonstration                              of very               good knowledge               on regression model.Demonstration of good knowledge on regression model.Demonstration of basic knowledge on regression model.Demonstration of poor knowledge on regression model.
Interpreting the coefficient of determination  Demonstration of outstanding knowledge on goodness of fit of the regression modelDemonstration of very good knowledge on goodness of fit of the regression modelDemonstration of good knowledge on goodness of fit of the regression model.Demonstration of basic knowledge on goodness of fit of the regression modelDemonstration of poor knowledge on goodness of fit of the regression model
Use of regression for predictionDemonstration                           of outstanding knowledge on usefulness of the regression model for prediction purposes.Demonstration               of very               good knowledge on usefulness of the regression model for prediction purposes.Demonstration                           of good knowledge usefulness of the regression model for prediction purposes.Demonstration                           of basic knowledge on usefulness of the regression model for prediction purposes.Demonstration of poor knowledge on usefulness of the regression model for prediction purposes.

Academic Integrity

Holmes Institute is committed to ensuring and upholding Academic Integrity, as Academic Integrity is integral to maintaining academic quality and the reputation of Holmes’ graduates. Accordingly, all assessment tasks need to comply with academic integrity guidelines. Table 1 identifies the six categories of Academic Integrity breaches. If you have any questions about Academic Integrity issues related to your assessment tasks, please consult your lecturer or tutor for relevant referencing guidelines and support resources. Many of these resources can also be found through the Study Sills link on Blackboard.

Academic Integrity breaches are a serious offence punishable by penalties that may range from deduction of marks, failure of the assessment task or unit involved, suspension of course enrolment, or cancellation of course enrolment.

Table 1: Six categories of Academic Integrity breaches

Plagiarism  Reproducing the work of someone else without attribution. When a student submits their own work on multiple occasions this is known as self-plagiarism.
Collusion  Working with one or more other individuals to complete an assignment, in a way that is not authorised.
Copying  Reproducing and submitting the work of another student, with or without their knowledge. If a student fails to take reasonable precautions to prevent their own original work from being copied, this may also be considered an offence.
ImpersonationFalsely presenting oneself, or engaging someone else to present as oneself, in an in-person examination.
Contract cheatingContracting a third party to complete an assessment task, generally in exchange for money or other manner of payment.
  Data fabrication and falsification  Manipulating or inventing data with the intent of supporting false conclusions, including manipulating images.

Source: INQAAHE, 2020

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