Program Name: MGB Batch: Oct22 Syd Term 2

Program Name: MGB Batch: Oct22 Syd Term 2

Test paper set: B Reflective Paper

Campus: Sydney Faculty Name: Prof Rajesh Tukdeo

Subject: Data Analytics Max. Marks 40%

To be submitted by :

Files to be uploaded can be MS Word / Excel. If more than one, file will be uploaded as zip file.

Soft Copy Submission Mettl and BlackBoard.

This test is in lieu of end term exam.

All rules as applicable to end term exam shall be followed.

Reproducing information from the text book / slides / course material will lead to honour code violation. Kindly adhere to honour code guidelines.

All other guidelines specified in the examination policy document are applicable.

S P Jain Honour Code for Academic Integrity during Examinations

S P Jain School of Global Management (SPJSGM) aims to sculpture Global Leaders who are consistently able to demonstrate the upmost professionalism and ethical integrity. This exam Honour Code reflects the standards which the School expects of all its students when taking exams.

Do note that cheating and plagiarism are considered extremely serious offenses and will be punished accordingly

Plagiarism: This includes falsely representing the ideas, words and facts or any part of other sources work as your own without properly acknowledging and referencing that source.

Cheating: This includes the unauthorized use of communications technology, internet access as well as communicating verbally or non-verbally with other students within the examination room.

Punishment for Violations: Punishments can vary from downgrading by 1 or 2 grade notches to suspension or even expulsion from the Course. Please be warned.

By signing on this Pledge below, you agree to:

Uphold the Principles and Values of SPJSGM as part of its Vision and Mission.

Act in a truthful manner with upmost professionalism and ethical integrity.

Refrain from any form of cheating and plagiarism.

__________________________________

Signed

Re-Exam Reflective Individual Assignment Sydney Campus

40 marks

Objective

This reflective individual assignment is focused around using Data Analytics to describe the current situation and potential problems for the business. Students are expected to download a dataset in Excel format of any domain of their choice. Their primary objective is to perform multiple linear regression for better decision making and submit a report about the insights found within the data. They are also expected to highlight any anomalies or issues identified within the data during the analysis process.

Steps to perform

Step No. Tasks to be performed Weightage marks

1 Students are required to download their datasets in Excel format from the online resources listed at the end of the document. Make sure that the dataset should be suitable for multiple linear regression i.e. it must have one dependent variable and multiple independent variables.

Once the dataset is selected and downloaded for analysis, describe data properties of each column within the dataset. If necessary, students can create new columns by doing any additional calculations e.g. new column Age using existing column Birth date etc. 10

2 Perform Exploratory descriptive analytics (EDA) using Excel and create basic correlation-based graphs and insights. EDA should be done very efficiently and every graph should be explained logically.

If required, perform data cleaning also. 10

Implement the following data analytics using Excel

3 Apply multiple linear regression on this data to predict numeric outcome and interpret the results. Also show residuals in the results.

Make sure that the regression should help you to identify R-Square, coefficients for line equation etc. 10

4 Prepare a detailed PDF report with abstract, introduction, domain of dataset and related objectives, framework, data collected, data cleaning, result execution, conclusion, along with screenshots must be submitted 10

What do I need to submit?

Original Excel dataset used - with any additional calculations (if used)

Excel file with all EDA and multiple linear regression

Detailed Report in PDF format

Important Guideline related to Plagiarism and Submission

Do not share your data, code, report with your friends or batch mates.

Do not ask someone to code for you.

Avoid using chatgpt and similar models.

Any plagiarism due to sharing/copying of data / analysis / material will result in failure.

Try to use different datasets than used by your batchmate to avoid penalties

Assignment Outcome

Understanding of effective usage of multiple linear regression for data driven decision making.

Data links (just for reference, you can choose your own preferred dataset as well)

https://www.telusinternational.com/insights/ai-data/article/10-open-datasets-for-linear-regressionhttps://college.cengage.com/mathematics/brase/understandable_statistics/7e/students/datasets/mlr/frames/frame.htmlhttps://data.world/datasets/regressionhttps://www.interviewquery.com/p/regression-datasets-and-projectshttps://www.quora.com/Where-can-I-find-data-sets-for-regressionKaggle: https://www.kaggle.com/datasets/category/businessUCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets.phpWorld Bank Open Data: https://data.worldbank.org/Google Dataset Search: https://datasetsearch.research.google.com/