This data analysis session focuses on the application of logical functions in Microsoft Excel, used for conditional analysis and decision-making.Review of Previous Concepts

The class began by reviewing previous tasks, specifically calculating discount prices, new sales prices, and total profits. It was clarified that while the dataset was for practice rather than real-world financial analysis, the formulas used—such as multiplying sales by discount rates and subtracting that from sales—were correctly applied.Logical Functions Overview

The speaker introduced logical functions as tools to compare values and return results based on whether a condition is true or false. Key functions covered include:

• IF: Checks if a condition is met and returns a specific value for “true” and another for “false”.
• AND: Returns true only if all specified conditions are met.
• OR: Returns true if at least one of the specified conditions is met.
• IFS: A newer function that handles multiple conditions without requiring nested IF statements.
• IFERROR: Used to manage errors by replacing them with a specified value.

Practical Applications

The participants worked through several examples, emphasizing the following:

• Score Grading: Using the IF function to grade student scores (e.g., “Pass” if ≥ 50, otherwise “Fail”).
• Nested IFs vs. IFS: To handle complex grading systems (e.g., A, B, C, or Fail), participants practiced both “nested IF” formulas (where IF functions are placed inside each other) and the more modern IFS function.
• Scholarship Eligibility: Using the AND function to require that multiple conditions (e.g., attendance ≥ 80% and exam score ≥ 75) be met simultaneously.
• Risk Assessment: Using the OR function to flag students at risk if their attendance is below 60% OR their exam score is below 50%.
• Combining Functions: The session demonstrated how to combine IF and AND functions to create more complex conditional logic for final approvals.

The session concluded by highlighting that these functions are foundational for data cleaning and diagnostic analysis, with more advanced predictive and prescriptive analysis planned for future classes.