ITEC202 Data Analytics and Visualisation Assignment

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Reference no: EM133023060

ITEC202 Data Analytics and Visualisation - Australian Catholic University

Assessment - Data Analytics Project

The principal goal of this project is to import a real-life data set, clean and tidy the data, and perform basic exploratory data analysis; all while using R Markdown to produce an HTML report that is fully reproducible.

Context
The purpose of this individual final project is to put to work the tools and knowledge that you gain throughout this course. This provides you with multiple benefits.

1. It will provide you with more experience using data wrangling tools on real life data sets.
2. It helps you become a self-directed learner. As a data analyst/scientist, a large part of your job is to self- direct your learning and interests to find unique and creative ways to find insights in data.
3. It starts to build your data analytics/science portfolio. Establishing a data science portfolio is a great way to show potential employers your ability to work with data.

Instructions
Download the Birthweight dataset: CSV file.

This dataset contains information on newborn babies and their parents. It contains mostly continuous variables (although some have only a few values e.g. number of cigarettes smoked per day) and is most useful for correlation and regression. The birthweights of the babies who mothers smoked have been adjusted slightly to exaggerate the differences between mothers who smoked and didn't smoke so students can see the difference more clearly in a scatterplot with gestational age and scatter colour coded by smoking status.

Project Report
You will write an R Markdown HTML report that provides the sections in the structure provided below. You will need to import, assess, clean & tidy the data, and then come up with your own research questions that you would like to answer from the data by performing exploratory data analysis and perform a predictive model. Try to be creative in your analysis and investigate the data in a way that your classmates most likely will not.

Attachment:- Data Analytics and Visualisation.rar

Verified Expert

This task provides a clear working procedure on data mining and predictive analysis. the birth weight of babies was taken as the dependent variables and simple linear regression model was performed to determine the significant predictors for birth weight. it is found that length of babies, gestation period, head circumference and smoker are significant predictors of birth weight

Reference no: EM133023060

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