Economic Statistics

Bachelor 2020/2021

Type: Compulsory course (International Business and Management Studies)

Area of studies: Management

Delivered by: Department of Economics

Where: St.Petersburg School of Economics and Management

When: 2 year, 3, 4 module

Mode of studies: offline

Instructors: Arsen Davitadze, Tatiana Rodionova, Elena Taraskina, Evgeny Zazdravnykh

Language: English

ECTS credits: 6

Contact hours: 60

Full Syllabus

Abstract

This course equips students with basic skills in statistical analysis in economics and management. Student learn principles of sampe design, testing hypotheses, estimation of correlations. Exercises are based on business cases and datasets from business.

Learning Objectives

be able to design sample for the survey or data collection
be able to use distributions for analytical purposes
be able to create statistical distributions
be able to test hypotheses
be able to estimate correlation coefs
be able to draw conclusions based on statistical analysis

Expected Learning Outcomes

to be able to apply quantitative research methods in the field of business studies
be able to demonstrate knowledge of descriptive statistics and data visualization
be able to calculate confidence intervals
be able to find probability distributions for discrete events
be able to estimate probability distributions for continuous events
be able to estimate parameters of proportions
be able to apply ANOVA to solve data analysis problems
be able to test hypotheses
be able to estimate confidence interval
be able to design sample for the further analysis

Course Contents

Introduction
Descriptive Statistics
Confidence Intervals
Testing Hypotheses
Compare Two Populations
ANOVA
Correlation
Descriptive Statistics of Proportions
Hypothesis Testing for Population Proportions
Goodness-of-Fit Tests and Contingency Analysis
Nonparametric Methods
Surveys

Assessment Elements

Seminar Activity
Home Assignments
We don't accept home assignments when the student sends us do- and log-file by email.
Oral Exam

Interim Assessment

Interim assessment (4 module)
0.2 * Home Assignments + 0.7 * Oral Exam + 0.1 * Seminar Activity

Bibliography

Recommended Core Bibliography

Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
Denis, D. J. (2016). Applied Univariate, Bivariate, and Multivariate Statistics. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1091881
Denis, Daniel J. (2015). Applied Univariate, Bivariate and Multivariate Statistics, John Wiley & Sons, Inc. https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=4338227
Statistics and Causality : Methods for Applied Empirical Research, edited by Wolfgang Wiedermann, and Eye, Alexander von, John Wiley & Sons, Incorporated, 2016. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=4530803.
Stowell, Sarah (2014). Using R for Statistics. Apress. https://link.springer.com/book/10.1007%2F978-1-4842-0139-8

Recommended Additional Bibliography

Bertail, P., Blanke, D., Cornillon, P.-A., & Matzner-Løber, E. (2019). Nonparametric Statistics : 3rd ISNPS, Avignon, France, June 2016. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2044916
Biswas, D. (2019). Probability and Statistics: Volume I. [N.p.]: New Central Book Agency. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2239779
Pearl, J., Glymour, M., & Jewell, N. P. (2016). Causal Inference in Statistics : A Primer. Chichester, West Sussex, UK: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1161971

Course Syllabus