Data Analysis Using Microsoft Excel

Course Number:

BA 169Z

Transcript Title:

Data Analysis Using Microsoft Excel

Created:

May 22, 2025

Updated:

May 22, 2025

Total Credits:

4

Lecture Hours:

20

Lecture / Lab Hours:

40

Lab Hours:

0

Satisfies Cultural Literacy requirement:

No

Satisfies General Education requirement:

No

Grading Options

A-F

Default Grading Options

A-F

Repeats available for credit:

0

Suggested Outcome Assessment Strategies

The determination of assessment strategies is generally left to the discretion of the instructor. Here are some strategies that you might consider when designing your course: writings (journals, self-reflections, pre writing exercises, essays), quizzes, tests, midterm and final exams, group projects, presentations (in person, videos, etc), self-assessments, experimentations, lab reports, peer critiques, responses (to texts, podcasts, videos, films, etc), student generated questions, Escape Room, interviews, and/or portfolios.

Course Activities and Design

The determination of teaching strategies used in the delivery of outcomes is generally left to the discretion of the instructor. Here are some strategies that you might consider when designing your course: lecture, small group/forum discussion, flipped classroom, dyads, oral presentation, role play, simulation scenarios, group projects, service learning projects, hands-on lab, peer review/workshops, cooperative learning (jigsaw, fishbowl), inquiry based instruction, differentiated instruction (learning centers), graphic organizers, etc.

Course Content

Outcome #1: Create and manage worksheets using appropriate data formatting.

• Creating and Navigating Worksheets
  • Worksheet Basics
  • Navigating Worksheets

• Data Entry and Organization

  • Efficient Data Input
  • Organizing Data

• Formatting Worksheets

  • Cell Formatting
  • Number and Data Formats
  • Conditional Formatting

• Managing Worksheet Layout

  • Adjusting Worksheet Structure
  • Setting Print Options

• Organizing and Validating Data

  • Sorting and Filtering Data
  • Data Validation

• Worksheet Protection and Security

  • Protecting Worksheets
  • Tracking Changes

• Advanced Features

  • Tables

  • Formulas Across Worksheets

Outcome #2: Construct formulas with relative, absolute, and mixed cell references.

• Introduction to Excel Formulas

  • Formula Basics
  • Operators in Formulas

• Understanding Cell References

  • Relative Cell References
  • Absolute Cell References
  • Mixed Cell References

• Constructing Formulas with Different References

  • Practical Examples
  • Copying Formulas Across Cells

• Applying References in Common Excel Functions

  • Functions Utilizing References
  • Examples with Dynamic Data

• Error Checking and Troubleshooting

  • Common Reference Errors
  • Formula Auditing Tools

• Real-World Applications

  • Financial Calculations
  • Data Analysis

Outcome #3: Analyze data using logical, lookup, mathematical, statistical, and text functions.

• Logical Functions

  • Overview of Logical Functions
  • Common Logical Functions
  • Practical Applications

• Lookup and Reference Functions

  • Introduction to Lookup Functions
  • Core Functions
  • Advanced Usage

• Mathematical Functions

  • Overview of Mathematical Functions
  • Key Functions
  • Practical Applications

• Statistical Functions

  • Introduction to Statistical Analysis
  • Essential Functions
  • Practical Applications

• Text Functions

  • Purpose of Text Functions
  • Common Text Functions
  • Applications

• Advanced Topics

  • Combining Functions
  • Data Validation and Error Handling

• Real-World Applications

  • Scenario Analysis
  • Data Reporting
  • Data Cleaning and Preparation

Outcome #4: Manipulate large volumes of data using datasets and tables.

• Working with Large Datasets

  • Dataset Basics
  • Data Navigation and Management

• Creating and Managing Tables

  • Table Basics
  • Table Features
  • Dynamic Table Ranges

• Sorting and Filtering Large Data

  • Sorting Options
  • Filtering Data

• Using Conditional Formatting on Large Data

  • Highlighting Key Data
  • Custom Rules

• Data Aggregation and Summarization

  • Subtotaling Data
  • Quick Analysis Tools

• Advanced Data Manipulation Tools

  • Sorting and Removing Duplicates
  • Splitting and Combining Data
  • Data Validation

• Pivot Tables and Pivot Charts

  • Introduction to Pivot Tables
  • Pivot Table Customization
  • Pivot Charts

• Advanced Techniques for Large Datasets

  • Dynamic Arrays
  • Using Power Query

• Real-World Applications

  • Data Analysis
  • Reporting
  • Data Cleaning and Preparation

Outcome #5: Interpret data using data visualization tools, including pivot tables and charts.

• Overview of Data Visualization in Excel

  • Introduction to Data Visualization
  • Understanding Data for Visualization

• Creating and Customizing Charts

  • Basic Chart Types
  • Advanced Chart Types
  • Chart Customization

• Using Pivot Tables for Data Analysis

  • Creating Pivot Tables
  • Customizing Pivot Tables
  • Using Slicers and Timelines

• Creating and Customizing Pivot Charts

  • Introduction to Pivot Charts
  • Customizing Pivot Charts

• Conditional Formatting for Visual Analysis

  • Highlighting Data Patterns
  • Custom Rules

• Dashboards and Interactive Reports

  • Combining Tools
  • Best Practices for Dashboards
  • Sharing Dashboards

• Advanced Visualization Tools

  • Dynamic Charting
  • Using Power Query and Power Pivot

• Best Practices for Data Visualization

  • Choosing the Right Chart
  • Enhancing Interpretability

• Real-World Applications

  • Trend Analysis
  • Comparative Analysis
  • Highlighting Insights

Suggested Texts and Materials

Open source: Beginning Excel, First Edition by Barbara Lave, Diane Shingledecker, Julie Romey, Noreen Brown, and Mary Schatz