Course Objectives:

A prime objective of the course is to introduce the students to the fundamentals of the Statistics and present techniques and basic results of the theory and illustrate these concepts with applications.

Attitudinal aims:

In addition to specific learning outcomes, the course aims to shape the attitudes of learners regarding the field of Statistics. Specifically, the course aims to

Motivate in students an intrinsic interest in statistical thinking.

Instill the belief that Statistics is important for scientific research.

Provide a foundation and motivation for exposure to statistical ideas subsequent to the course.

Learning outcomes :

Each numbered item states a learning aim for the course, and the items that follow indicate the learning outcomes (or objectives) through which that aim could be deemed to have been satisfied.

  1. Demonstrate the ability to apply fundamental concepts in exploratory data analysis.
  • Distinguish between different types of data.
  • Interpret examples of methods for summarising data sets, including common graphical tools (such as boxplots, histograms and stemplots) and summary statistics (such as mean, median, mode, variance and IQR).
  • Assess which methods for summarising a data set are most appropriate to highlight interesting features of the data.
  • Identify the features that describe a data distribution.
  • Use an appropriate software tool for data summary and exploratory data analysis
  • Assesment Criteria

  • Sessional: 20 (Assignment 10, Attendance 05, Quiz 05)
  • Mid-Term Exam: 30
  • Final-Term Exam: 50

Course Material