DTS001TC Data Analytic for Entrepreneurship

DTS001TC Data Analytic for Entrepreneurship

Resit Coursework

Submission deadline:

Percentage in final mark: 100%

Learning outcomes assessed:

A: Preprocess, analyse and interpret data using a modern computer package

B: Summarize and visualize data using a modern computer package

C: Present findings to a business audience in a suitable format

Late policy: 5% of the total marks available for the assessment shall be deducted from the assessment mark for each working day after the submission date, up to a maximum of five working days

Risks:

Please read the coursework instructions and requirements carefully. Not following these instructions and requirements may result in loss of marks.

Plagiarism results in award of ZERO mark.

The formal procedure for submitting coursework at XJTLU is strictly followed. Submission link on Learning Mall will be provided in due course. The submission timestamp on Learning Mall will be used to check late submission.

All students must download their file and check that it is viewable after submission. Documents may become corrupted during the uploading process (e.g. due to slow internet connections). However, students themselves are responsible for submitting a functional and correct file for assessments.

Overview

In this coursework, you are required to complete two tasks based on the given dataset and submit a compressed document that includes two files:

1. Task1: An Excel file (in xlsx file) containing your visualization and modeling process and results for the given dataset.

2. Task2: A report (in pdf file) analyzing the visualization and modeling results.

The assignment must be submitted via Learning Mall Online to the correct drop box. Only electronic submission is accepted and no hard copy submission.

Task 1 (50 marks)

You are given a dataset of children's heights and parents' heights. You need to design and create your visualization and model based on the dataset. The visualization will show the impact of different factors on the children’s height, while the model needs to present the relationship between multiple factors and children’s height.  Here are task specifications:

Target for visualization: You are asked to use excel to create a visualization that complete the following tasks

O Clean and preprocess the original dataset (9 marks)

O Select appropriate charts and data formats for visualizing the data (8 marks)

O Show the impact of the father’s height on children’s height (3 marks)

O Show the impact of the mother’s height on children’s height (3 marks)

O Show the impact of the children’s sex on children’s height (3 marks)

O Show the impact of the number of kids in the family on children’s height (3 marks)

Target for model: You are asked to use excel to fit a model that can present the relationship between multiple factors and children’s height based on the given dataset. Your model needs to complete the following tasks.

o Choose the appropriate dependent variable for the appropriate model (13 marks)

o Strive for high R-Square as much as possible (8 marks)

The submitted Excel file should include:

o The original dataset

o The dataset after data preprocessing

o All visualized tables and charts

o Summary output of the constructed model

Detailed Requirements:

o The formulas and functions used in data preprocessing needs to be retained in your xlsx file. You need to demonstrate through formulas how the processed data was transformed step by step.

o Visual charts and tables need to be generated by Excel and remain in an editable state in your xlsx file. Screenshots will not be accepted.

Additional notes:

o The use of  add-ins that have not been mentioned in lecture is allowed, but it is necessary to refer the source and ensure that the add-ins is publicly available

o It is allowed to use newly constructed features during the model constructing, but these features must be based on the original dataset, and the process of constructing the new features needs to be retained.