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Fundamentals of Descriptive Analysis and Data Visualization
Fundamentals of Descriptive Analysis and Data Visualization
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In this course, students will understand the basic concepts of data and descriptive statistics, including the classification of qualitative and quantitative data, and the use of measures of central tendency (mean, median, mode) and dispersion (range, standard deviation, and coefficient of variation) to summarize and interpret datasets, making it possible to identify patterns and key characteristics for decision-making.
The module explores how to choose appropriate visualizations, matching chart types to specific objectives, such as comparison, composition, distribution, and relationships between variables. Best practices in visual integrity, simplicity, audience fit, and preserving data accuracy are covered, ensuring that charts and dashboards communicate information clearly, honestly, and efficiently.
Finally, students will learn data storytelling techniques and how to build interactive dashboards using tools like Excel, Power BI, Tableau, R, and Python. The focus is on turning raw data into actionable insights, presenting information in a narrative format that supports interpretation and accelerates strategic decision-making in organizations.
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