Paper CQP 106

Quantitative Skills and Data Analytics

This subject is designed to equip the learner with practical technological skills, which will enable him or her to analyze data and provide meaningful business insights. The subject introduces the learner to quantitative tools and use of statistical tests and tools such as ANOVA.

On completion, a candidate should be able to

The learner is expected to:
Successfully determine and collect the type of data required.
Develop data wrangling skills (clean, prepare and sample).
Develop skills on how to choose the best analytical method.
Successfully develop conclusions and insights on the data.
Demonstrate data visualization skills.

Content

1
Introduction to Analytics
Collect, clean, analyze data and prepare reports
1. Concept of data analytics
2. Types of data
3. Data collection, cleaning and analysis
4. Communication of data
5. Types of software to use in analytics
2
Statistical Data Analysis using SPSS or JASP
Use SPSS or JASP for data modelling
1. Introduction to SPSS or JASP.
2. Define variables.
3. Import data.
4. Transform data.
5. Perform descriptive analysis.
6. Perform statistical tests – T- tests, ANOVA, correlations, linear/multilinear regression models
3
Structured Query Language (SQL)
Use SQL for database manipulation
1. Understand databases using Structured Query Language (SQL).
2. Logical design of a database
3. Relational Database Management Systems
4. Data definition language
4
MS Excel Spreadsheets for data analysis
Data modelling
1. Loading data from different sources.
2. Cleaning data.
3. Sorting data.
4. Use Excel functions to perform data analysis.
5. Data visualization through charts, graphs, pivot tables
6. Other data modelling tools (Python and R)
5
Data Analytics Project
Undertake a project
1. Data collection from multiple sources.
2. Exploratory data analysis.
3. Data wrangling.
4. Statistical analysis.
5. Data modelling.
6. Data visualization.
7. Presentation of data analysis report