# Statistics for Business Analytics using MS Excel

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

Language: english

Note: 4.5/5 (267 notes) 34,185 students

Last update: 2022-01-15

## What you’ll 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, BinomialÂ  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.

## Requirements

• Only a PC with any version of Excel installed is needed for this course on “Statistics for Business Analytics using MS Excel”

## Description

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

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 Sectionâ€™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.

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!

Cheers

## Who this course is for

• Anyone curious to master Excel for Business Analysis in a short span of time
• Business Analysts/ Managers who want to expand on the current set of skills

## Course content

• Introduction
• Welcome to the course
• Course resources
• Excel for data analytics
• Milestone
• 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
• 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
• 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
• Popular Excel charts
• The final milestone!
• Bonus Lecture

IBM Cybersecurity Analyst [Coursera with IBM]

Time remaining or 707 enrolls left

 Don’t miss any coupons by joining our Telegram group