Using Excel for Exploratory Data Analysis (S-IT0072)

Individuals who want to learn the principles of exploratory data analysis and how to apply Excel’s features for data exploration.

To extract the most from the course, students should have good grasp of Excel’s features such as inserting formulas, fixed and moveable referencing, inserting and customizing charts, applying conditional formatting using formulas, and data validation principles. Additionally, good understanding of operations such as percentages, proportions, raising to a power, averages and the use of logical operators (greater than, less than, not equal to) is required.

• Describe the purpose and principles of Exploratory Data Analysis and learn the main descriptive statistics.
• Learn the principles and functions used to subset data in Excel (logical indexing and conditional selection, FILTER) and for implementing conditional aggregations using direct methods (SUMIF, AVERAGEIF, MINIF).
• Learn to expand Excel’s capabilities using LET functions.
• Create visualizations to summarize data and identify trends: histograms, scatter plots, bar charts, box-plots.

This course provides you with the tools to conduct exploratory data analysis (EDA) using advanced excel functions and statistical charts. After completing the course, participants will be able to use Excel effectively to derive insights from their data and to communicate their observations effectively using charts in Excel.

• Exploratory data analysis, descriptive statistics, and Excel’s functions to compute measures of tendency and spread.
• Logical operations and developing conditional decision making (IF,SWITCH and the conditional aggregation functions).
• Filtering arrays and selecting data using logical indexing.
• Use the data analysis toolpak add-in for correlation and histogram analysis, and use native charts such as scatter, bar charts and box-plots for data spread visualisation.