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Statistics using Excel

Master statistical and analytical techniques using Excel — designed for professionals who want to go deeper into data-driven decision making.

What You’ll Learn

In this 2-day hands-on training, you'll gain the skills to explore, analyze, and visualize business data using Excel. Perfect for business users, analysts, and decision-makers who want to apply analytics in real-world contexts.

Data Analysis & Statistics

Understand key statistical concepts, data types, and measures like mean, median, variance, and standard deviation using Excel functions.

Data Visualization

Create meaningful charts and visuals — from histograms to dynamic dashboards — that bring insights to life.

PivotTables & KPIs

Summarize and filter business data, identify trends and performance indicators, and present metrics effectively to stakeholders.

Descriptive Analytics

Perform correlation, covariance, probability, and distribution analysis for decision support and trend understanding.

Interactive Dashboards

Design visually compelling Excel dashboards using slicers, conditional formatting, and layout best practices.

Course Modules

This 2-day program blends statistics and Excel skills for professionals who want to analyze business data confidently. Each module is paired with practical retail examples to ensure real-world relevance.

📘 Chapter 1: Introduction to Statistics

  • Role of statistics in business decisions
  • Descriptive vs. inferential analytics
  • Retail Example: Analyzing footfall data to understand sales patterns

📘 Chapter 2: Types of Data

  • Categorical vs. numerical data and levels of measurement
  • Retail Example: Classifying customers by membership tier and spending

📘 Chapter 3: Data Collection Methods

  • Primary vs. secondary data sources and survey design
  • Retail Example: Using customer feedback and loyalty records

📘 Chapter 4: Measures of Central Tendency

  • Mean, median, and mode for business insights
  • Retail Example: Average basket size across stores

📘 Chapter 5: Measures of Dispersion

  • Range, variance, and standard deviation to study variability
  • Retail Example: Variability in daily sales across locations

📘 Chapter 6: Frequency Distribution

  • Creating frequency tables and histograms
  • Retail Example: Frequency of products sold in different price bands

📘 Chapter 7: Data Visualization

  • Designing bar, pie, and line charts for clarity
  • Retail Example: Visualizing monthly sales and top categories

📘 Chapter 8: Percentiles & Quartiles

  • Ranking and benchmarking with percentiles in Excel
  • Retail Example: Identifying 90th percentile spenders among loyalty customers

📘 Chapter 9: Correlation & Covariance

  • Identifying relationships between variables using scatter plots
  • Retail Example: Correlation between discount % and units sold

📘 Chapter 10: Basics of Probability

  • Understanding event likelihood and independence
  • Retail Example: Estimating stockout probability from past trends

📘 Chapter 11: Normal Distribution

  • Using bell curves, Z-scores, and standardization in analysis
  • Retail Example: Modeling delivery or customer wait times
Author Photo

About the Author

Jayen Thakker is the Founder of MetricMinds.in and a Business Analyst with years of experience helping organizations make sense of data through visualization and analytics. He has mentored 1000+ learners and conducted multiple workshops in Data Analytics, Excel, Tableau, and Power BI. This 2-day course helps professionals build analytical depth using Excel’s most powerful techniques.

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