Data and Statistical Analytics Using Microsoft Excel
Date: Tuesday, August 11, 2026
Instructor: Stephen M. Yoss
| Begin Time: |
9:00am Pacific Time
10:00am Mountain Time
11:00am Central Time
12:00pm Eastern Time |
| CPE Credit: |
2 hours for CPAs |
|
The role of the financial professional has shifted from reporting on the past to predicting the future, yet many practitioners still rely on manual, static workflows that fail to capture the full story within their data. This course bridges the gap between traditional accounting and modern data science by utilizing Excel’s most powerful analytical engines to turn raw numbers into defensible business intelligence. We will move beyond simple averages, exploring how to use the Analysis ToolPak for deep statistical dives and leveraging Dynamic Arrays to build fluid, auto-updating models that respond to changing business conditions in real time.
Participants will explore a modern analytics workflow that balances classic statistical rigor with cutting-edge efficiency. We will examine how to implement regression analysis for more accurate budgeting, utilize advanced forecasting functions to anticipate market shifts, and even leverage AI-assisted insights to find hidden patterns in sprawling datasets. By the end of this session, you will be able to distinguish between mere “data entry” and “data discovery,” providing your firm or organization with the high-level analysis required to navigate an increasingly complex economic landscape.
Who Should Attend
CPAs and financial professionals seeking to modernize their data analysis and forecasting capabilities.
Topics Covered
- Statistical Foundations: Using the Analysis ToolPak for Insight
- Modern Modeling: Leveraging Dynamic Arrays for Live Analytics
- Predictive Budgeting: Applying Regression and Forecasting Functions
- The 2026 Toolkit: AI Insights and Python Integration Basics
Learning Objectives
- List the primary categories of business analytics and their practical applications in accounting
- Utilize the Analysis ToolPak to generate descriptive statistics and analyze data distribution patterns
- Implement regression analysis within Excel to identify and quantify key business performance drivers
- Use Dynamic Array functions to create flexible and automated statistical summary reports
- Analyze emerging AI and Python integrations to determine their utility for advanced modeling
Level
Basic
Instructional Method
Group: Internet-based
NASBA Field of Study
Computer Software & Applications (2 hours)
Program Prerequisites
None
Advance Preparation
None
