Excel for Advanced Statistical Modelling – 1 Day Session in Ottawa

Group Discounts:

• Save 10% when registering 3 or more participants
• Save 15% when registering 10 or more participants

Duration: 1 Full Day (9:00 AM – 5:00 PM)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, beverages, and light snacks included

This course focuses on using Microsoft Excel for advanced statistical analysis and modeling without requiring programming knowledge. It covers key statistical concepts, analytical tools, and modeling techniques that can be applied directly in business, research, and operational contexts. The session emphasizes practical understanding, interpretation of results, and building confidence in using Excel for complex data analysis within a single day.

Learning Objectives

By the end of this course, you will:

• Understand advanced statistical concepts used in data analysis
• Apply statistical modeling techniques using Excel
• Analyze relationships and trends within datasets
• Interpret regression and hypothesis testing results
• Build simple predictive and forecasting models
• Improve data-driven decision-making confidence
• Avoid common mistakes in statistical analysis

Target Audience

• Business analysts
• Finance and operations professionals
• Researchers and analysts
• Managers working with data
• Professionals using Excel for reporting and analysis
• Anyone seeking advanced analytical skills in Excel

Why is it right fit for you:

This course bridges the gap between statistics and practical Excel usage, making advanced analysis accessible without complex software or coding. The trainer brings hands-on experience in data analysis and business modeling, ensuring concepts are explained clearly and applied realistically. The course content is carefully structured to deliver maximum value within a single day.

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Looking to upskill your workforce efficiently?
This program can be delivered as an in-house session customized to your organization’s data, industry, and analytical needs. Examples and models can be aligned with real business scenarios for higher relevance. Flexible delivery options ensure learning outcomes match organizational goals.

📧 Contact us today to schedule a customized in-house, face-to-face session: [email protected]

Info: • Review of key statistical concepts used in modeling
• Understanding data types and distributions
• Importance of data accuracy and preparation
• Icebreaker

Info: • Cleaning and structuring data for analysis
• Descriptive statistics and summary measures
• Identifying trends, outliers, and patterns
• Case study

Info: • Normal, binomial, and other common distributions
• Probability concepts used in decision-making
• Interpreting distribution outputs in Excel
• Simulation

Info: • Understanding relationships between variables
• Simple and multiple regression concepts
• Interpreting regression results for insights
• Case study

Info: • Null and alternative hypotheses
• Confidence intervals and significance levels
• Business interpretation of test results
• Activity

Info: • Time series concepts and trend analysis
• Forecasting methods using historical data
• Evaluating model accuracy and limitations
• Simulation

Info: • Translating statistical outputs into insights
• Communicating findings to stakeholders
• Common modeling errors and how to avoid them
• Role play

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