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HIM6007 Statistics for Business Decisions Assessment Group Assignment

Assessment Details and Submission GuidelinesTrimesterT3 2024Unit CodeHIM6007Unit TitleStatistics for Business DecisionsAssessment TypeGroup AssignmentDue Date + time:

Due on 31/01/2025

11.59 pm (Melb/ Sydney time)

Purpose of the assessment (with ULO Mapping)

Students are required to show understanding of the principles and techniques of business research and statistical analysis taught in the course.

Integrate theoretical and practical knowledge from the discipline of Statistics for Business Decision Making to solve business needs; Synthesise advanced theoretical, practical knowledge fromthe discipline of statistics for business decision and be able to apply statistical tools and techniques to solve business problems; Critically analyse a scenario and apply and justify statistical techniques to solve business problems and the explain the results to a range of stakeholders. Work well autonomously as well as within groupsettings to identify and apply statistical solutions to a business scenario Weight40%Total MarksAssignment (40 marks)Word limitN/A, except where specifiedSubmission Guidelines

All work must be submitted on Blackboard by the duedate along witha completed Assignment Cover Page. The assignment must be in MS Word formatunless otherwise specified. Academic Integrity InformationHolmes Institute is committed to ensuring and upholding academic integrity. All assessments must comply with academic integrity guidelines. Please learn about academic integrity and consult your teachers with any questions. Violating academic integrity is serious and punishable by penalties that range fromdeduction of marks, failure of the assessment task or unit involved, suspension of course enrolment, or cancellation of course enrolment.Penalties

All work must be submitted on Blackboard by the duedate and time,along with a completed Assessment Cover Page. Late penalties apply. Your answers must be based on Holmes Institute syllabus of this unit. Outside sources may notamount to more than 10% of any answer and must be correctly referenced in full. Over-reliance on outside sources will be penalised Reference sources must be cited in the textof the reportand listed appropriately at the end in a reference list using Holmes Institute Adapted Harvard Referencing. Penalties are associated with incorrect citation and referencing. Group Assignment Guidelines and Specifications

PART A (20 marks)

Assume your group is the data analytics team in a renowned Australian company. The company offers its assistance to a distinct group of clients, including (but not limited to) public listed companies, small businesses, and educational institutions. The company has undertaken several data analysis projects, all based on multiple regression analysis. One such project is related to the real estate market in Australia, and the team needs to answer the following research question based on their analysis.

Research question:

How do different factors, such as the size of the land, the number of bedrooms, the distance to the nearest secondary school, and the number of garage spaces, influence the selling price of residential properties?

Task

Create a data set (in Excel) that satisfies the following conditions. (You are required to upload the data file separately).

Minimum number of observations — 100 observations. The data set should be based on houses soldfrom 01/07/2024 onwards. (To verify the data set, you are required to add a hyperlink to each property’s details from the real estate websites that you used.) (5 marks)

Questions

Conduct a descriptive statistical analysis in Excel using the data analysis tool. Create a table that includes the following descriptive statistics for each variable in your data set: mean, median, mode, variance, standard deviation, skewness, kurtosis, and coefficient of variation. (4 marks)

Provide a brief commentary on the descriptive statistics you calculated. Describe the characteristics of the distribution for each variable based on these statistics. (4 marks) Create an appropriate graph to illustrate the distribution of the number of bedrooms in your data set. (2 marks) Derive a suitable graph to represent the relationship between the dependent variable and the land size in your data set and comment on the identified relationship. (3 marks) Based on the data set, perform correlation analysis, and based on the correlation coefficients in the correlation output, assess the correlation between explanatory variables and check for the possibility of multi collinearity . (2 marks) Part B (15 marks)

Assume your group is the data analytics team in a renowned Australian company (CSIRO). You are given the dataset derived from their recent research. This data compiles fortnightly observations of Logan’s Dam, a small body of water located near Gatton, in Southeast Queensland. It consists of measurements taken by CSIRO and the Urban Water Security Research Alliance with the intention of measuring the impact of the application of an evaporation-reducing monolayer on the dam’s surface.

The measurements recorded indicate the biomasses present (P.plankton and Crustacean) in the dam, chemicals present in the dam (Ammonia and Phosphorus) , as well as more general measures of water quality such as pH and temperature.

Research Question:

What are the factors (variables) that significantly impact on the health of the dam in relation to water Turbidity, and what measures should be taken to ensure its effective maintenance?

Task

Note: Refer the data given the excel file “HIM6007 T3 Dam_Water_Quality_Dataset”

Based on the data set, perform regression analysis and correlation analysis, and answer the questions given below. (Hint: Turbidity as dependent variable)

Derive the multiple regression equation. (2 marks) Interpret the meaning of all the coefficients in the regression equation. (3 marks) Interpret the calculated coefficient of determination. (2 marks) At a 5% significance level, test the overall model significance. (2 marks) At a 5% significance level, assess the significance of the independent variables in the model. (3 marks) Based on the correlation coefficients in the correlation output, assess the correlation between explanatory variables and check for the possibility of multicollinearity. (3 marks) PART C (5 marks)

Based on the answers in PART A above, write a summary of your analysis addressing the research question (100 -150 words). (3 marks) Based on the answers in PART B above, write a summary of your analysis addressing the research question (100 words). (2 marks) Marking criteria

Marking criteriaWeightingPART A Data collection (Excel spreadsheet)5 marksDescriptive statistical analysis and review (Questions i andii)8 marksGraphical representations of data (Questions iii and iv)5 markscorrelation output and interpretation of coefficients (Questions v)2 marksPART B Derive the multiple regression equation and interpret the meaning of all the coefficients in the regression equation (Question i and ii)5 marksInterpretation of coefficient of determination (Question iii)2 marksAssessing the overall model significance (Questioni and v)5 marksExamining the correlation between explanatory variables and checking for the possibility of multicollinearity (Question iv)3 marksPART C Summary (i and ii)5 marksTOTAL Weight40 Marks

Assessment Feedback to the Student:

Marking Rubric

ExcellentVery GoodGoodSatisfactoryUnsatisfactoryPerformingDemonstration ofDemonstration ofDemonstration ofDemonstration ofDemonstration ofdescriptiveoutstandingvery goodgood knowledgebasic knowledgepoor knowledge onstatistical analysisknowledge onknowledge onon descriptiveon descriptivedescriptive measuresand review of thedescriptivedescriptivemeasuresmeasures calculated valuesmeasuresmeasures Deriving suitableDemonstration ofDemonstration ofDemonstration ofDemonstration ofDemonstration of poorgraph to representoutstandingvery goodgood knowledgebasic knowledge onknowledge onthe relationship between variables

knowledge

on presentation of data

knowledge on presentation of data

using presentation

on presentation of data using suitable

chart types.

presentation of

data

using suitable chart

presentation of data using suitable chart

types.

using suitable chartof data using types. types.suitable chart types. Deriving multiple regression equation based on the regression output.

Demonstration of outstanding knowledge

on regression model estimation and interpretation

Demonstration of very good knowledge on regression model estimation and interpretationDemonstration of good knowledge on regression model estimation and interpretationDemonstration of basic knowledge on regression model estimation and interpretation

Demonstration of poor knowledge on regression

model estimation and interpretation

Interpreting the calculated coefficient of determination.

Demonstration of outstanding knowledge

on coefficient of determination calculation and interpretation of relationship between

variables

Demonstration of very good knowledge on coefficient of determination calculation and interpretation of relationshipDemonstration of good knowledge on coefficient of determination calculation and interpretation of relationship between variables

Demonstration of basic knowledge on coefficient of determination calculation and interpretation of relationship

between variables

Demonstration of poor knowledge on coefficient of determination calculation and interpretation of relationship between

variables

between variables Assessing the overall model significance.Demonstration of outstanding knowledge on model significance

Demonstration of very good

knowledge on model significance

Demonstration of good knowledge on model

significance

Demonstration of basic knowledge on model significanceDemonstration of poorknowledge on model significanceAssessing the significance of independent variables in the model.Demonstration of outstanding knowledge on significance of independent variables.

Demonstration of very good knowledge on significance of independent

variables.

Demonstration of good knowledge on significance of independent

variables.

Demonstration of basic knowledge on significance of independent

variables.

Demonstration of poorknowledge on

significance of independent variables.

Examining the correlation between explanatory variables and check the possibility of

multicollinearity.

Demonstration of outstanding knowledge on correlation

coefficient calculation, interpretation of relationship between variables and assessing

multicollinearity.

Demonstration of very good knowledge on correlation coefficient calculation, interpretation of relationship between variables and assessing

multicollinearity.

Demonstration of good knowledge correlation coefficient calculation, interpretation of relationship between variables and assessing

multicollinearity.

Demonstration of basic knowledge on correlation coefficient calculation, interpretation of relationship between variables and assessing

multicollinearity.

Demonstration of poorknowledge on

correlation coefficient calculation, interpretation of relationship between variables and assessing multicollinearity.

Addressing research questions based on data analysisDemonstration of outstanding knowledge on addressing research questions based on data analysis.

Demonstration of very good knowledge on addressing research questions basedon

data analysis.

Demonstration of good knowledge on addressing research questions based on data

analysis.

Demonstration of basic knowledge on addressing research questions basedon data analysis.Demonstration of poor knowledge on addressing research questions based on data analysis.

Your final submission is due Friday of week ten before midnight.

The following penalties will apply:

Late submissions -5% per day. No cover sheet OR inaccuracies on the cover sheet -10% No title page -10% Inaccuracies in referencing OR incomplete referencing OR not in Holmes-adapted-Harvard style -10% Student Assessment Citation and Referencing Rules

Holmes Institute has implemented a revised Harvard approach to referencing. The following rules apply:

Reference sources in assignments are limited to sources that provide full-text access to the source’s content for lecturers and markers. The reference list must be located on a separate page at the end of the essay and titled: “References”. The reference list must include the details of all the in-text citations, arranged A-Z alphabetically by author’s surname with each reference numbered (1 to 10, etc.) and each reference MUST include a hyperlink to the full text of the cited reference source. For example: Hawking, P., McCarthy, B. & Stein, A. 2004. Second Wave ERP Education, Journal of Information Systems Education, Fall, http://jise.org/Volume15/n3/JISEv15n3p327.pdf

All assignments must include in-text citations to the listed references. These must include the surname of the author/s or name of the authoring body, year of publication, page number of the content, and paragraph where the content can be found. For example, “The company decided to implement an enterprise-wide data warehouse business intelligence strategy (Hawking et al., 2004, p3(4)).”

Non-Adherence to Referencing Rules

Where students do not follow the above rules, penalties apply:

For students who submit assignments that do not comply with all aspects of the rules, a 10% penalty will be applied. Students who do not comply with guidelines BUT their citations are ‘fake’ will be reported for academic misconduct. 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

PlagiarismReproducing the work of someone elsewithout attribution. Whena student submits their own work on multiple occasions this is known as self- plagiarism.CollusionWorking with one or more other individuals to complete an assignment, in a way that is not authorised.CopyingReproducing and submitting the work of another student, with or without their knowledge. If a studentfails to takereasonable 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 falsificationManipulating or inventing data with the intent of supporting false conclusions, including manipulating images.

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