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Regular version of the site
Bachelor 2019/2020

Data Analysis in Spreadsheets

Type: Elective course (Economics)
Area of studies: Economics
When: 4 year, 1 module
Mode of studies: distance learning
Language: English
ECTS credits: 4
Contact hours: 2

Course Syllabus

Abstract

The course “Data analysis with Spreadsheets” is designed to provide students with basic knowledge and skills of data analysis with Spreadsheets, in particular Microsoft Excel. The course begins with an introduction to basics of Spreadsheets, data types and predefined and conditional functions. Then students will learn how pivot tables are created and analyzed and how statistical analysis is performed. The final part of the course is devoted to techniques of data visualization using Spreadsheets. The course is supported by online platform for education DataCamp (www.datacamp.com). Students are expected to watch online lectures and complete assignments using the platform. Some lectures and final examination are provided by lecturers of National Research University Higher School of Economics.
Learning Objectives

Learning Objectives

  • Know basic principles of working with Spreadsheets.
  • Import data, make basic manipulation with it to prepare data for analysis, apply basic methods of preliminary data analysis and visualize data.
  • Have skills of interpreting the result of data analysis and understanding limitation and relevance of applied methods.
Expected Learning Outcomes

Expected Learning Outcomes

  • Know basic data types in Spreadsheets. Is able to determine data types and convert them. Have skills of conditional formatting.
  • Know basic functions to calculate summary statistics. Is able to build pivot tables. Have skills of data visualizing depending on data and task type.
Course Contents

Course Contents

  • Spreadsheet Basics
    1. Basics of Spreadsheets and data types. 2. Predefined and conditional functions.
  • Data Analysis and Visualization with Spreadsheets
    3. Pivot tables. 4. Statistics in Spreadsheets. 5. Data visualization
Assessment Elements

Assessment Elements

  • non-blocking Self-study work
  • non-blocking Exam
    Final student assessment is a project, that is performed in a team of no more than 2 people. Each team uses provided dataset of collets their own data, define research question and apply one or a combination of the learnt methods of data analysis with Spreadsheets. As a result of the project each team write down the report and prepare working file. The grade for the exam includes the grade for the report, grade for the working file and the grade for answering questions.
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.6 * Exam + 0.4 * Self-study work
Bibliography

Bibliography

Recommended Core Bibliography

  • Goldmeier, J. (2014). Advanced Excel Essentials. [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=898783
  • Slager, D. (2016). Essential Excel 2016 : A Step-by-Step Guide. [Berkeley]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1361984

Recommended Additional Bibliography

  • Schmuller, J. (2013). Statistical Analysis with Excel For Dummies (Vol. 3rd ed). New York: For Dummies. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=566464