Course Content

Declaring advanced functions, complex data manipulation, pattern matching, writing efficient programs, point estimation, confidence interval and hypothesis testing, using a statistical software with quality control tools for statistical process control, generating quality control charts, multiple linear regression, model diagnostics, generate reports for statistical analysis.

All the concepts are demonstrated using R software.

Pre-requisites: DSC3013

Recommended Texts

• Lander, J.P. (2017). R for Everyone: Advanced Analytics and Graphics. 2nd Ed. Addison-Wesley Data & Analytics Series.

• de Micheaux, P.L., Drouilhet, R. and Liquet, B. (2014). The R Software: Fundamentals of Programming and Statistical Analysis. 2013 Ed., Springer.

• Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design, 1st Ed. No Starch Press.

Course Evaluation

• Continuous Assesments (Mid Exam/Assignments): 40%
• End Semester Examination: 60%