Data Analysis with Spreadsheet Program

A practical course that equips students with essential skills in data-driven decision-making using Microsoft Excel. The course covers the complete data analytics workflow: importing and cleaning data, exploratory data analysis, statistical analysis, visualization, and professional reporting of insights.

Students develop proficiency in modern Excel capabilities including Power Query, PivotTables, and Power Pivot. Through hands-on labs and a capstone group project, students learn to transform raw data into actionable business insights and communicate findings to diverse audiences.

Full syllabus Labs & assignments Resources

Schedule

Fifteen weeks, alternating lecture and lab. Lab weeks are group progress presentations. Weeks marked TBD are not yet finalized and their materials are not published.

Week	Type	Topic	Materials	Assessment
1	Lecture	Course Introduction & Excel Basics Course overview: objectives, assessment, project-based structure Group project requirements: team formation, topic selection, timeline Excel interface, the analytics workflow, essential formulas (SUM, AVERAGE, COUNT, IF, VLOOKUP) Relative vs absolute cell references	Slides	—
2	Lab	Lab 1 — Excel Basics with Product Inventory Hands-on practice with SUM, AVERAGE, COUNT, IF, COUNTIF, VLOOKUP Group Progress Report 1: topic selection, problem statement, research questions	—	Lab 1 + Progress Report 1
3	Lecture	Data Import & Cleaning Import from CSV, Excel, and web using Get Data (Power Query) Power Query Editor: Change Type, Remove Duplicates, Filter Rows Replace Values, Trim & Clean, Remove Blank Rows Handling missing values; loading to worksheet and Data Model	Slides	—
4	Lab	Lab 2 — Data Import & Cleaning with Store Sales Orders Import CSV/Excel, apply Power Query transformations on the Store Sales Orders dataset Group Progress Report 2: data quality assessment and cleaning methodology	—	Lab 2 + Progress Report 2
5	Lecture	Exploratory Data Analysis Descriptive statistics and summary tables Data segmentation and filtering PivotTables: layout, grouping, calculated fields Reading patterns in aggregate data	Slides	—
6	Lab	Lab 3 — EDA & PivotTables Descriptive analysis and PivotTables on project data Group Progress Report 3: descriptive statistics summary and key patterns	—	Lab 3 + Progress Report 3
7	Lecture	Data Visualization & Dashboards Chart types and when to use each Design principles for effective data visualizations Interactive dashboards with slicers and PivotCharts Conditional formatting and sparklines	Slides	—
8	Lab	Lab 4 — Visualization & Dashboard Create charts and build interactive dashboards from project data Group Progress Report 4: visual analysis and preliminary dashboard prototype	—	Lab 4 + Progress Report 4
9	Lecture	Statistical Analysis & Regression Hypothesis testing basics and t-tests in Excel Correlation and scatter plots Simple and multiple linear regression using the Analysis ToolPak Interpreting coefficients, R², and residuals	Slides	—
10	Assessment	Midterm Exam Computer-based exam (90 minutes) Covers Weeks 1–9: Excel basics, Power Query, EDA, visualization, statistics	—	Midterm Exam — 30%
11	Lab	Lab 5 — Statistical Analysis TBD Apply correlation, regression, and hypothesis testing to project data Group Progress Report 5: statistical hypotheses, results, and interpretation	—	Lab 5 + Progress Report 5
12	Lecture	Professional Reporting & Communication TBD Report structure and writing for different audiences Presenting insights effectively Overleaf / LaTeX workflow for formal reports	—	—
13	Lab	Final Project Work I TBD Complete analysis, build visualizations and dashboards, draft report Project Checkpoint: full analysis + comprehensive dashboard + draft report	—	Project Checkpoint
14	Lab	Final Project Work II TBD Refine analysis, finalise dashboards, complete written reports Peer review and feedback	—	Project Refinement
15	Assessment	Final Presentations TBD Group presentations (15 min) + Q&A (5 min) Final submission of all project materials	—	Final Project — 50%

Teaching staff

Dr. Trong-Nghia Nguyen

Course Instructor

nghiant@neu.edu.vn

Room 1613, Building A1

Office hours: By appointment

Personal website

MSc. Le Duy Khanh

Teaching Assistant

khanhld@neu.edu.vn

Lab troubleshooting and homework help

Faculty profile