Lesson’s Learning Outcomes
After completion of this lesson, learners will:
- Understand the Definition of Data Analysis: Learners will be able to define data analysis and explain its significance in transforming raw data into actionable insights.
- Recognize the Importance of Data Analysis in Daily Life: Learners will identify simple, real-life examples of data analysis, such as budgeting and tracking fitness progress.
- Comprehend the Role of Data Analysis in QA and QM: Learners will understand how data analysis is crucial for quality assurance and quality management, particularly in improving product and service quality.
- Identify Key Concepts in Data Analysis: Learners will differentiate between qualitative and quantitative data, understanding the applications and limitations of each type.
- Familiarize Themselves with Data Collection Methods: Learners will learn various data collection methods, including surveys, observations, and records, and know when to apply each method.
- Ensure Data Quality: Learners will understand the importance of data accuracy and completeness, and learn techniques for validating and verifying data quality.
- Analyze Case Studies: Learners will study real-world examples of data analysis in education, such as improving teaching effectiveness and enhancing student retention.
- Develop Skills in Data Interpretation: Learners will gain the ability to interpret data using basic statistical concepts, such as averages, variation measures, and probability.
- Utilize User-Friendly Tools: Learners will become familiar with tools for data analysis, including navigating the software, applying basic functions, and creating charts.
- Apply Data Analysis in Educational Settings: Learners will learn how to apply data analysis techniques to enhance educational quality assurance and management.
- Engage in Reflective Practice: Learners will be encouraged to reflect on their own data analysis practices, identify areas for improvement, and develop strategies for professional growth.
Authors
This lesson was developed by the QA-SURE Team at the South East European University (SEEU in North Macedonia.
Lesson’s Reading
Translated Reading
Learning Resources for Curious Minds
Introduction to Data Analysis: https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-learn-data-science-scratch/
Role of Data Analysis in Quality Assurance: https://www.isixsigma.com/tools-templates/data-collection/data-collection-and-analysis-quality-improvement/
Basic Concepts of Data Types and Collection Methods: https://www.qualtrics.com/experience-management/research/data-collection-methods/
Ensuring Data Quality: https://www.talend.com/resources/data-quality-importance/
Fundamental Statistical Concepts: https://www.statsoft.com/Textbook/Basic-Statistics
Interpreting Data with Graphs and Charts: https://www.tableau.com/learn/articles/best-beautiful-data-visualization-examples
Using Excel for Data Analysis: https://www.excel-easy.com/data-analysis.html
Implementing Data Analysis in QA and QM: https://asq.org/quality-resources/data-analysis
Case Studies on Data Analysis in Education: https://www.edsurge.com/news/2019-02-13-how-data-analysis-is-transforming-education
Continuous Improvement with Data Analysis: https://www.isixsigma.com/implementation/basics/plan-do-check-act-pdca-cycle/
