Introduction & Objectives :

This course is graduate level for other disciplines.Statistical analysis is a basic requirement in order to analyse the phenomenon related to all sectors.This course aims to produce skills related to descriptive as well as inferential statistical analysis.Use of index number regression ,sampling and time series has vital impotance to analyse and decision making theories related to agriculture, economics and business statistics.

The aim is to train students intensively in both theoretical and practical aspects of statistics, to bring them in contact with basic concepts and methods and to create a problem-solving attitude with the aid of statistical methodology.

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

Recommended books:

• probability and statistics for engineer and scientists by Walpole..
• Introduction to statistical theory by sher Muhammad chaudhry

Time table:

Monday & Tuesday :12:30-2:00