27598 - Statistical Methods for Business Analysis

Learning outcomes

This course provide a practical introduction to the issues involved in the design and analysis of sample surveys planned to support firm decisions.
The main learning goals are: to familiarize students with several of the well known statistical sampling methods for finite populations; to familiarize students with the planning of quality control systems.

Course contents

PART A
Inference in finite population sampling: design based inference; simple random sampling with and without replacement; unequal probability sampling; the Horvitz Thompson estimator. Stratified random sampling. The estimation of the sample size. Cluster sampling. Quotient  estimator.

PART B
Statistical process control: Shewhart control charts; control charts for variable; control charts for attributes; the role of the power function and the Average Run Length (ARL) function on the design of the control charts; CUSUM and EWMA charts.
Acceptance sampling: acceptance sampling for attributes; the Operative Curve (OC) of a sampling plan; simple sampling; rectification schemes.
Capability analysis: the general framework; some capability indices; some important issues when using capability indices.

Readings/Bibliography

PART A
Sharon Lohr, “Sampling: design and analysis”, Pacific Grove, Duxbury press, 1999.

PART B and PART C
D.C Montgomery, Statistical quality control, McGraw-Hill, 2007.

Some additional readings will be indicated during the course.

Teaching methods

Each topic covered in the lectures will be followed by exercises in practical classes.

Assessment methods

Written test and a facultative oral examination

Office hours

See the website of Carlo Trivisano