The course provides a rigorous foundation in the principle of probability and mathematical statistics underlying statistical inference in the feild of economics and business.Special emphasis is given to the study of parametric families of distributions,univariate as well as multivariate, and to basic asymptotic for sample averages.This course is a prerequisite for the lecture Advance Statistics 2, which focuses on the methods of statistical inferences including parameter estimation and hypothesis testing. Furthermore, it provides the foundation for specialization courses in statistics and econometrics( Time series analysis,Statistics for Financial Markets, Micro-econometrics, Multivariate Statistics, etc.)

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

Recommended Books

1. Thompson, B. (2006). Foundations of behavioral statistics. New York, N) Guilford Press

2. R. Mark Sirkin (2006) "Statistics for the Social Sciences SAGE. publishers.

Assesment Criteria

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

Time table:

Tuesday :12:30-2:00

Wednesday :2:30-4:00