MDA511: Mathematical and Statistical Methods Assignment Help for Melbourne Institute

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Assessment Details and Submission Guidelines

Unit Code

MDA511

Unit Title

Mathematical and Statistical Methods

Term, Year

T2, 2023

Assessment Type

Formative Assignment 1, Individual

Assessment Title

Australian Weather Statistical Data and Interpretation

Purpose of the  

assessment (with  ULO Mapping)

This assignment assessesthe following Unit Learning Outcomes;studentsshouldbe  able to demonstrate their achievements in them.

a. Develop knowledge and skills in using statistics to interpret data.

Weight

10% of the total assessment

Total Marks

25

Word limit

Minimum 700 words

Due Date

Week 3, Monday, 31st July 2023, 23:59 PM

Submission

Guidelines

All work must be submitted on Moodle by the due date.

The assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font, and 2 cm margins on all four sides of your page with appropriate section headings.  Reference sources must be cited in the text of the report and listed appropriately  at the end in a reference list using IEEE referencing style.

Students must ensure before submission of the final version of the assignment that  the similarity percentage as computed by Turnitin must be less than 10%.  Assignments with more than 10% similarity may not be considered for marking.

Extension

If an extension of time to submit work is required, a Special Consideration Application  must be submitted directly on AMS. You must submit this application three working days prior to the due date of the assignment. Further information is available at: https://www.mit.edu.au/about-us/governance/institute-rules-policies-and plans/policies-procedures-and-guidelines/assessment-policy.

Academic

Misconduct

Academic Misconduct is a serious offense. Depending on the seriousness of the case, penalties can vary from a written warning or zero marks to exclusion from the course orrescinding the degree. Students should make themselvesfamiliar with the full policy  and procedure available at:  

https://www.mit.edu.au/about-mit/institute-publications/policies-procedures-and guidelines/AcademicIntegrityPolicyAndProcedure.  

For further information, please refer to the Academic Integrity Section in your Unit  Description.

Prepared by: Dr Anies Hannawati Moderated by: Dr Md Asad Asaduzzaman July, 2023

2023 T2 Mathematical and Statistical Methods Page 2 of 3 ASSIGNMENT DESCRIPTION

The main aims of this task are to provide students with the ability to carry out self-directed research and obtain  trustworthy weather information from reputable sources. Students will acquire the skills needed to precisely  collect, comprehend, and handle data, and utilise this data to generate insightful inferences. This procedure  will allow students to acquire a comprehensive understanding of the data, the analytical process, and the art  of presenting their findings in an accurate and efficient manner. Additionally, the final submission is expected  to include high-quality bibliographies that reinforce the deductions derived from the data.

Task 1 Data Gathering and Descriptive Analysis [10 marks]

As a requirement for this task, you need to collect weather statistics for the Australian suburb where you  reside. You can do this by visiting the website of the Australian Bureau of Meteorology at  http://www.bom.gov.au. Extract weather data for a twelve-month period between July 2022 and June 2023,  focusing on mean temperature and humidity data for either the morning or afternoon data. Once you have  collected the necessary data, your task is to create tables and graphs of weather statistics for your chosen  locations. In your report, describe how you obtained the data from the website and explain your tables and  graphs in detail. This includes providing a more comprehensive analysis of the graphs, such as identifying any  specific weather patterns and possible correlations among them.

Task 2 Mathematical Model and Derivative [10 marks]

In this task, your objective is to create a mathematical model function for both data sets. This involves  providing a detailed explanation to justify the choice of the model and explaining the importance of developing  the model. Additionally, you should plot the derivatives of the functions, show all calculations and formulas  used, and provide an explanation of the use of the derivative function. Ensure that your explanations are  comprehensive and provide a clear understanding of how the derivatives were obtained. This will enable  readers to understand the reasoning behind your work and how the derivatives are related to the original  functions. You could utilise any relevant software tools like Phyton or Microsoft Excel to perform calculations and create charts or graphs. Ensure to use appropriate units of measurement and terminology throughout  your work. To ensure the accuracy and reliability of your findings, it is recommended to refer to at least three  reliable sources such as journals, conference papers, websites, or other reputable sources published or  updated within the last five years (2018-2023).  

MARKING CRITERIA

 

Task

Description

Marks

Task 1

Data Gathering and  Descriptive Analysis

Weather data are provided accurately.

Written report regarding gathering the data.

Descriptive analysis of the given data, including explanations of  weather patterns and possible correlations.

10

Task 2

Mathematical Model  and Derivative

Develop mathematical models that are supported by clear  justifications and explanations.

Provide and explain the derivatives of the functions with clear  justifications supporting your calculations.

10

Reference Style and  Presentation

Follow IEEE reference style and should have both in-text  citations and reference list.  

Nice presentation of the report including format report, spelling, and grammar.

2.5

2.5

Total

25

Prepared by: Dr Anies Hannawati Moderated by: Dr Md Asad Asaduzzaman July, 2023

2023 T2 Mathematical and Statistical Methods Page 3 of 3 MARKING RUBRIC

 

Grades

>=80%

70%-79%

60% – 69%

50% – 59%

<50%

Task 1

Data Gathering  and Descriptive  Analysis

The report is  

exceptional in  terms of data  collection,  

graph design,  analysis, and  

written report  structure. It  

shows a  

thorough  

understanding  of weather  

statistics and  

provides  

insightful  

observations of  the data.

The report is  

very good in  

terms of data  collection,  

graph design,  analysis, and  

written report  structure. It  

shows a good  understanding  of weather  

statistics and  

provides some  insightful  

observations of  the data.

The report is  

good in terms  of data  

collection,  

graph design,  analysis, and  

written report  structure. It  

shows a basic  understanding  of weather  

statistics and  

provides some  observations of  the data.

The report is  

satisfactory in  terms of data  collection,  

graph design,  analysis, and  

written report  structure. It  

shows a limited  understanding  of weather  

statistics and  

provides  

minimal  

observations of  the data.

The report is  

unsatisfactory  in terms of data  collection,  

graph design,  analysis, and  

written report  structure. It  

shows a poor  

understanding  of the weather  statistics and  

provides no  

observations of  the data.

Task 2

Mathematical  Model and  

Derivative

Mathematical  models are  

clear, well

justified, and  

include  

accurate  

derivatives that  support  

calculations  

and  

demonstrate a  comprehensive  understanding  of the  

concepts.

Mathematical  models are  

mostly clear  

and justified,  

with mostly  

accurate  

derivatives that  support  

calculations  

and  

demonstrate a  good  

understanding  of the  

concepts.

Adequate  

mathematical  models with  

some  

justifications  

and mostly  

supported  

derivatives that  demonstrate a  basic  

understanding  of the  

concepts.

Basic  

mathematical  models with  

limited  

justification  

and partially

supported  

derivatives that  demonstrate a  limited  

understanding  of the  

concepts.

Mathematical  models are  

incomplete or  incorrect, with  little or no  

justification,  

and  

unsupported  

derivatives that  demonstrate a  poor  

understanding  of the  

concepts.

Reference

Style and  

Presentation

Clear styles  

with an  

excellent  

source of  

references.  

The report is  

presented  

professionally.

Clear  

referencing  

style.

The report is  

written  

properly with

some minor  

mistakes.

Generally good  referencing  

style.

The report is  

mostly good,

but some  

structure or  

presentation  

problems.

Unclear  

referencing  

style.

The report is  

presented  

acceptably.

Lacks  

consistency  

with many  

errors.

The report is  

presented  

carelessly with  poor structure.

Prepared by: Dr Anies Hannawati Moderated by: Dr Md Asad Asaduzzaman July, 2023