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ETC1010: Introduction to Data Analysis

1 Unit Synopsis

Introduction to principles and techniques for modelling actuarial, business and economic data. Con-cepts and practice in taking "data from the wild", reading different formats, tidying, and wrangling it into shape for analysis. Building models and making useful visualizations to achieve effective data-driven decision-making. Learn how to find data to solve problems. Build oral and written communication skills. Hands-on learning, with some team work projects.

2 Unit Objectives

On successful completion of this unit, you should be able to:

1. Learn to read different data formats, learn about tidy data and wrangling techniques

2. Apply effective visualization and modelling to understand relationships between variables, and make decisions with data

3. Develop communication skills using reproducible reporting.

3 Unit Outline

1. Introduction to the language of data analysis: R, Rmarkdown

2. Tidy data principles and data wrangling

3. Grammar of graphics

4. Data visualization

5. Relational data; R projects

6. Handling missing values

7. Web scraping; R function

8. Linear regression models

9. Decision trees

10. Text analysis

11. Social network analysis

12. Project presentations

4 Assessment

Note: All assignments are due on the corresponding week on Monday 8pm.

5 Computing

● R

● Rstudio

● Rstudio Cloud

6 Reading/Textbooks

● R for Data Science Hadley Wickham and Garrett Grolemund http://r4ds.had.co.nz

● Text Mining with R Julia Silge and David Robinson https://www.tidytextmining.com

● Other online resources as prescribed, and staff members’ notes.