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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 2015 ADVANCED EXCEL APPLICATIONS ELECTIVE 3 0 0 4

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ÖZLEM KIREN GÜRLER

Offered to

Econometrics Econometrics (Evening)

Course Objective

The aim of this course is to enable students to effectively perform data analysis they may encounter in professional life using Excel. The course focuses on developing skills in calculation, reporting, summarization, and analysis through advanced Excel functions, macros, and data visualization tools.

Learning Outcomes of the Course Unit

1   1. To be able to use Excel functions effectively to perform calculations, classifications, filtering, and sorting on data. 2   2. To be able to conduct complex data analyses using advanced formulas and nested functions. 3   3. To be able to analyze large data sets and generate meaningful reports using pivot tables and summary tables. 4   4. To be able to write Excel macros (VBA) to automate repetitive tasks and enhance time management. 5   5. To be able to create charts and dashboards by applying data visualization techniques. 6   6. To be able to perform decision support analyses through real-life business scenarios. 7   7. To be able to apply data cleaning and validation methods to ensure data accuracy and integrity. 8   8. To be able to integrate Excel with other office software to prepare and present professional reports.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 1 Introduction and Review of Basic Excel Knowledge 2 2 Calculations with Basic Functions: SUM, AVERAGE, MAX, MIN, IF, SUMIF, IFS, and other basic functions with real-life examples 3 3 Data Validation and Conditional Formatting: Restricting data entry, automatic alerts, and data analysis with color-coded highlights 4 4 Advanced Formulas and Functions: Nested functions, text functions (LEFT, RIGHT, MID, etc.), date and time functions (TODAY, NOW, COUNTIF, etc.) 5 5 Lookup and Reference Functions: VLOOKUP, HLOOKUP, INDEX, MATCH, XLOOKUP, and relational data analysis 6 6 Data Visualization with Charts: Chart types: bar, line, pie, area, radar; chart design, labels, and trendlines 7 7 Using Pivot Tables: Data summarization, grouping, slicers, filtering, and cross-tab analysis½ 8 8 Data Analysis Tools Goal Seek, Scenario Manager 9 9 Advanced Filtering and Data Cleaning Techniques: Custom filters, removing duplicates, managing empty cells 10 10 Interactive Tables with Form Controls: Drop-down lists, checkboxes, sliders; basic elements of dashboards 11 11 Introduction to Macros and VBA: Recording macros, using the basic VBA editor 12 12 Automation Scenarios with VBA: Triggering actions with buttons, creating user-defined functions (UDFs) 13 13 Dashboard Design and Project Work: Interactive dashboards and student project kickoff 14 14 Final Evaluation and Future Discussions

Recomended or Required Reading

Ileri Düzey Excel, Excel 2016, 2019, 2021 ve Microsoft 365, Ömer Bağcı Ileri Excel Öğrenmenin Kısayolu, Hakan Yandım Microsoft Excel Data Analysis and Business Modeling (Business Skills) 5th Edition by Wayne Winston

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 STT TERM WORK (SEMESTER) 2 MTE MIDTERM EXAM 3 MTEG MIDTERM GRADE STT * 0.50 +MTE * 0.50 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 6 RST RESIT 7 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

ozlem.kiren@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 14 1 14 Preparation for final exam 1 10 10 Preparing assignments 1 25 25 Preparing presentations 1 5 5 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 100

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 1 LO.2 1 LO.3 1 LO.4 1 LO.5 1 LO.6 1 LO.7 1 LO.8