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Economic Statistics

2023/2024
Учебный год
ENG
Обучение ведется на английском языке
4
Кредиты
Статус:
Курс обязательный
Когда читается:
1-й курс, 1, 4 модуль

Преподаватели

Course Syllabus

Abstract

The course is designed to give students the basic tools of collecting, analyzing, presenting, and interpreting data. Students will learn how to apply statistical information and quantitative methods to the workplace.
Learning Objectives

Learning Objectives

  • The course has the following objectives: • To teach students to use primary and secondary data sources properly and to correctly interpret and apply statistical information • To correctly present statistical data in tables and charts • To calculate numeric descriptive measures To involve students into the statistical process starting from analyzing the data and going up to final conclusions and recommendations. • To engage students into practical use of statistical methods for decision making through case analysis, problem solving and individual project creation.
Expected Learning Outcomes

Expected Learning Outcomes

  • Describe the importance of statistics.
  • Differentiate between descriptive statistics and inferential statistics
  • Explain the various data types
  • Describe variables and types of measurement scales
  • Summarize qualitative data by constructing a frequency distribution
  • Construct and interpret a pie chart and a bar chart
  • Summarize quantitative data by constructing a frequency distribution
  • Construct and interpret a stem-and-leaf diagram
  • Calculate and interpret measures of central location
  • Interpret a percentile and a boxplot
  • Calculate and interpret measures of dispersion
  • Explain mean-variance analysis and the Sharpe ratio
  • Construct and interpret a scatterplot
  • Calculate and interpret covariance between two variables
  • Calculate and interpret the correlation between two variables
Course Contents

Course Contents

  • 1. What is Statistics?
  • 2. Generalizing statistical indicators: absolute and relative values. Indexes.
  • 3. Presenting Data in Tables and Charts
  • 4. Numerical Descriptive measure
  • 5. Correlation analysis
Assessment Elements

Assessment Elements

  • non-blocking Quizzes for every topic
    Short quizzes in class. They will take from 10 to 15 minutes, depending on the complexity
  • non-blocking Test
    The test is carried out in the classroom (remotely in case of switching to online learning), in writing, 80 minutes. The test is a closed book, closed notes. Using course materials is not allowed.
  • non-blocking GROUP PROJECTS ON SEMINARS
    The group form of control, for a mini-group of 4-5 people within the study group, is not retaken, those missed for a good reason are redistributed, those missed for an unexcused reason are evaluated at 0 points. Each mini-group is tasked to present a data source given to them in advance, describing it in terms of the data it contains: the size of the database, the number and type of features, homogeneity, data collection methods, the presence of omissions and errors, and possible use for statistical research. The presentation is carried out orally in the form of a defense, evaluated by the teacher on a 10-point system.
  • non-blocking GROUP PROJECT
    The task is for groups of 5-6 people. 1. Obtain a database. 2. Present your database: explain how the data was collected, what is your unit of observation, what variables do you have. 3. Present summary statistics for your variables. 4. What valuable insights we can get from your data? You can use correlations to explore relationship between variables, calculate aggregated measures or indexes, present your data with charts and/or tables. Try to communicate your insight using visualization and/or informative and easily perceived indicator.
Interim Assessment

Interim Assessment

  • 2023/2024 1st module
    0.25 * GROUP PROJECT + 0.25 * GROUP PROJECTS ON SEMINARS + 0.25 * Quizzes for every topic + 0.25 * Test
  • 2023/2024 4th module
    1 * 2023/2024 1st module
Bibliography

Bibliography

Recommended Core Bibliography

  • Business statistics : A Decision-Making Approach, Groebner, D. F., 1993

Recommended Additional 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.
  • Essentials of business statistics, Jaggia, S., 2014
  • 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.
  • Inequality, polarization and poverty : advances in distributional analysis, Chakravarty, S. R., 2009