Statistics II

COURSE OVERVIEW
This course is part of a sequence starting with the course “Statistics I”. Their overall goal is to introduce
quantitative methods as a way to extract information from the data with the ultimate goal of improving
managerial decisions.

LEARNING OBJECTIVES
Upon successful completion of this course, students should be able to complete the following tasks:
- Understand the basic concepts of sampling and inferential statistics and compute various inferential
statistics.
- Perform hypothesis testing applying probability theory, quantifying the probability of committing an error
and distinguishing the different types of statistical errors.
- Formalize regression models, perform the estimation of parameters, and interpret the results.
- Understand the differences among various statistical techniques and identify the appropriate technique
to be used in a specific problem.
- Explore data numerically and graphically, communicate the results in business and academic
environments.
- Perceive the usefulness of statistics and be aware of the ethical issues pertaining to data collection,
analysis, and reporting.

TEACHING AND LEARNING METHODOLOGY
The learning methodology is based on theory lectures and practice sessions. The lectures describe a
structured set of selected relevant concepts along with illustrative examples. Students are invited to
participate in class discussions as a way to successfully master the material. The practice sessions offer
numerous numerical exercises requiring the use the techniques covered in the theory lectures.

COURSE CONTENT
1. Introduction
2. Random sampling and sampling distributions
3. Properties of estimators
4. Confidence interval estimation: single sample and two samples
5. Tests of hypothesis: single sample and two samples
6. Simple and Multiple regression analysis and additional topics in regression analysis.