Бакалавриат
2021/2022
Экономическая статистика
Статус:
Курс обязательный (Международный бизнес и менеджмент)
Направление:
38.03.02. Менеджмент
Кто читает:
Департамент менеджмента
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
2-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
5
Контактные часы:
50
Course 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
- be able to apply ANOVA to solve data analysis problems
- be able to calculate confidence intervals
- be able to demonstrate knowledge of descriptive statistics and data visualization
- be able to design sample for the further analysis
- be able to estimate confidence interval
- be able to estimate parameters of proportions
- be able to estimate probability distributions for continuous events
- be able to find probability distributions for discrete events
- be able to test hypotheses
- to be able to apply quantitative research methods in the field of business studies
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
Interim Assessment
- 2021/2022 2nd module0.15 * Home Assignments + 0.7 * Oral Exam + 0.15 * 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.
- 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
- 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
- Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.
- 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
- 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