Statistics for Business Analytics using MS Excel

Learn how probability & statistics is used for business & business strategy. Make statistical business models in Excel

4.51 (267 reviews)
Data & Analytics
11 hours
Jan 2022
last update
regular price

What you will learn

Learn the concepts of Probability and statistics required for making business decisions

Use concept of Statistical inference to make statistics-based judgement of business scenarios

Knowledge of all the essential Excel formulas required for Business Analysis

Implement predictive ML models such as simple and multiple linear regression to predict outcomes to real world problems

Knowledge of data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data

Learnr important probability distributions such as Normal distribution, Poisson distribution, Exponential distribution, Binomial  distribution etc

Solve business case-studies with Excel's data analytics tools such as solver, goal seek, scenario manager, etc

Learn about important data processing topics like outlier treatment, missing value imputation, variable transformation, and correlation.


You're looking for a complete course on understanding Statistics for Business Analytics, right?

You've found the right Statistics for Business Analytics using MS Excel course! This course will teach you data-driven decision-making and the use of analytical and statistical methods in business settings.

After completing this course you will be able to:

  • Understand how to formulate a business problem as an analytics problem

  • Summarize business data into tables and charts to communicate information effectively

  • Make predictive machine learning model to predict business outcomes

  • Use statistical concepts to reach business decisions

  • Interpret the results of statistical models for formulating strategy

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this course on Statistics for Business Analytics in Excel.

If you are a business manager, or business analyst or an executive, or a student who wants to learn Statistics concepts and apply analytics techniques to real-world problems of the Business business function, this course will give you a solid base for Statistics and Analytics by teaching you the most popular Business analysis models and how to implement it them in MS Excel.

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

  • Theoretical concepts and use cases of different Statistical models required for evaluating business models

  • Step-by-step instructions on implementing business models in MS Excel

  • Downloadable Excel files containing data and solutions used in MS Excel

  • Class notes and assignments to revise and practice the concepts in MS Excel

The practical classes where we create the model for each of these strategies are something that differentiates this course from any other course available online.

What makes us qualified to teach you?

The course is taught by Abhishek (MBA - FMS Delhi, B. Tech - IIT Roorkee) and Pukhraj (MBA - IIM Ahmedabad, B. Tech - IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of analytics in this course. We have in-hand experience in Business Analysis and MS Excel.

We are also the creators of some of the most popular online courses - with over 600,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts like Business Statistics and Analytics in MS Excel. Each section contains a practice assignment for you to practically implement your learning on Business Analysis in MS Excel.

What is covered in this course?

The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tool which is MS Excel. This will aid the students who have no prior coding background to learn and implement  Statistics and Analytics concepts to actually solve real-world problems of Business Analysis.

Let me give you a brief overview of the course

  • Part 1 - Excel for data analytics

In the first section, i.e. Excel for data analytics, we will learn how to use excel for data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data.

We will also cover how to use different types of charts to visualize the data and discover hidden data patterns.

  • Part 2 - Statistics foundations for business analysts

Then, in the second section, i.e. Statistics foundations for business analysts, we will start learning about the core concepts of Business Analytics i.e. probability and probability distribution. We will look at important probability distributions used in a business setting such as Normal distribution, Poisson distribution, Exponential distribution, Binomial  distribution etc

These concepts form the foundation of data analytics, machine learning, and deep learning.

  • Part 3 - Statistical Decision making

Once we have covered the basics of probability, in the 3rd section, i.e. Statistical Decision making we will discuss some advanced concepts related to sample testing i.e. hypothesis testing.

These are the concepts that differentiate a beginner from a pro!

  • Part 4 - Optimizing Business Models

In the fourth section, i.e. Optimizing Business Models we will learn how to solve common business problems with the help of excel's data analytics tools such as solver, goal seek, scenario manager, etc.

  • Part 5 - Preprocessing Data for ML models

In this section, you will learn what actions you need to take step by step to get the data and then prepare it for analysis, these steps are very important. We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bivariate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation, and correlation.

  • Part 6 - Linear regression model for predicting metrics

This section starts with simple linear regression and then covers multiple linear regression.

We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.

I am pretty confident that the course will give you the necessary knowledge on Business Statistics and Business Analysis using MS Excel, and the skillsets of a Business Analyst to immediately see practical benefits in your workplace.

Go ahead and click the enroll button, and I'll see you in lesson 1 of this Statistics for Business Analytics course!


Start-Tech Academy


Statistics for Business Analytics using MS Excel - Screenshot_01Statistics for Business Analytics using MS Excel - Screenshot_02Statistics for Business Analytics using MS Excel - Screenshot_03Statistics for Business Analytics using MS Excel - Screenshot_04



Welcome to the course
Course resources

Excel for data analytics

Basic Formula Operations
Mathematical Formulas - Part 1
Mathematical Formulas - Part 2
Textual Formulas - Part 1
Textual Formulas - Part 2
Logical Formulas
Date-Time Formulas
Lookup Formulas ( V Lookup, Hlookup, Index-Match )
Data Tools - Part 1
Data Tools - Part 2
Pivot Tables

Introduction to probability

Probability module - Introduction
Basics of probability
Calculating Probability in Excel - Part 1
Calculating Probability in Excel - Part 2
Important laws of probability
Implementing laws of probability in Excel

Probability distribution concepts

Concepts of probability distribution
Measures of probability distribution in Excel
Discreet vs continuous probability distribution
Using probablity distribution

Types of discreet probability distribution

Discreet Uniform probability distribution
Discreet binomial probability distribution
Binomial - Practical session
Discreet Poisson probability distribution
Poisson - Practical session

Types of continuous probablity distribution

Continuous probability distribution - Introduction
Uniform continuous probability distribution
Normal distribution
Normal distribution - Practical
Exponential distribution
Exponential distribution - Practical

Statistical Inference

Module Introduction
Sampling and Types of Sampling
Point Estimation
Excel - How to do random sampling
Excel - Point Estimation
Sampling Distributions
Excel - Demo of key results
Interval Estimation
Excel - Interval Estimation for mean
Excel - Interval Estimation for proportion
How to determine sample size?
Sample case study

Hypothesis Testing

What is Hypothesis testing?
Type 1 and Type 2 errors
The process of hypothesis testing Part-1
The process of hypothesis testing Part-2
How to find the p-value?
Excel - Statistical Formulas for T distribution
Excel - Statistical Formulas for Z distribution
Vaccination case study
Ecommerce site case study

Optimizing business models

Module introduction
Goal-seek and Scenario Manager in Excel
Solver in Excel
Different Solving methods of Excel Solver
Solving a Transportation problem
Price Skimming
Excel - Price Skimming model
Concept of Customer lifetime Value
Excel - Calculating customer lifetime value

Predictive analytics - Preparing the Data

Module introduction
Gathering Business Knowledge
Data Exploration
The Data and the Data Dictionary
Univariate analysis and EDD
Discriptive Data Analytics in Excel
Outlier Treatment
Identifying and Treating Outliers in Excel
Missing Value Imputation
Identifying and Treating missing values in Excel
Variable Transformation in Excel
Dummy variable creation: Handling qualitative data
Dummy Variable Creation in Excel
Correlation Analysis
Creating Correlation Matrix in Excel

Building a Linear Regression Model

The Problem Statement
Basic Equations and Ordinary Least Squares (OLS) method
Assessing accuracy of predicted coefficients
Assessing Model Accuracy RSE and R squared
Creating Simple Linear Regression model
Multiple Linear Regression
The F - statistic
Interpreting results of Categorical variables
Creating Multiple Linear Regression model

Bonus Section

The final milestone!
Congratulations & About your certificate


June 24, 2022
Some of the important content is missing like finding accuracy at end of predicting values and how to improve the model by adjusting which parameters. Rest of the part, the course has covered many topics which were under the carpet before. Thank you for making such kind of course and keep making such detailed courses.
May 28, 2022
This is a good learning platform that provides all the basic training and calculation needed in solving optimization problems in statistics.
April 6, 2022
content quality is good but content delivery is very bad. completing this course is such an boring process for me but still I have to do it. I hope you will improve it in future
October 11, 2021
Very good. Equations and how they are used manually gives an understanding of what is actually happening which is not necessarily the case when using the software,
October 1, 2021
Content is very good, but it is quite difficult to understand the accent. Caption doesn`t help either.



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