Data & Analytics


Excel Analytics: Linear Regression Analysis in MS Excel

Linear Regression analysis in Excel. Analytics in Excel includes regression analysis, Goal seek and What-if analysis

4.36 (552 reviews)

Excel Analytics: Linear Regression Analysis in MS Excel



2,5 heures au


Nov 2020

Last Update
Regular Price

What you will learn

Learn how to solve real life problem using the Linear Regression technique

Preliminary analysis of data using Univariate analysis before running Linear regression

Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm

Understand how to interpret the result of Linear Regression model and translate them into actionable insight

Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem

Course contains a end-to-end DIY project to implement your learnings from the lectures


You're looking for a complete Linear Regression course that teaches you everything you need to create a Linear Regression model in Excel, right?

You've found the right Linear Regression course!

After completing this course you will be able to:

· Identify the business problem which can be solved using linear regression technique of Machine Learning.

· Create a linear regression model in Excel and analyze its result.

· Confidently practice, discuss and understand Machine Learning concepts

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.

If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular technique of machine learning, which is Linear Regression

Why should you choose this course?

This course covers all the steps that one should take while solving a business problem through linear regression.

Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

What makes us qualified to teach you?

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course

We are also the creators of some of the most popular online courses - with over 150,000 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. Each section contains a practice assignment for you to practically implement your learning.

What is covered in this course?

This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems.

Below are the course contents of this course on Linear Regression:

· Section 1 - Basics of Statistics

This section is divided into five different lectures starting from types of data then types of statistics

then graphical representations to describe the data and then a lecture on measures of center like mean

median and mode and lastly measures of dispersion like range and standard deviation

· Section 2 - Data Preprocessing

In this section you will learn what actions you need to take a step by step to get the data and then

prepare it for the 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 bi-variate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation and correlation.

· Section 3 - Regression Model

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.

We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results, what are other variations to the ordinary least squared method and how do we finally interpret the result to find out the answer to a business problem.

By the end of this course, your confidence in creating a regression model in R will soar. You'll have a thorough understanding of how to use regression modelling to create predictive models and solve business problems.

Go ahead and click the enroll button, and I'll see you in lesson 1!


Start-Tech Academy


Below is a list of popular FAQs of students who want to start their Machine learning journey-

What is Machine Learning?

Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

What is the Linear regression technique of Machine learning?

Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value.

Linear regression is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y). More specifically, that y can be calculated from a linear combination of the input variables (x).

When there is a single input variable (x), the method is referred to as simple linear regression.

When there are multiple input variables, the method is known as multiple linear regression.

Why learn Linear regression technique of Machine learning?

There are four reasons to learn Linear regression technique of Machine learning:

1. Linear Regression is the most popular machine learning technique

2. Linear Regression has fairly good prediction accuracy

3. Linear Regression is simple to implement and easy to interpret

4. It gives you a firm base to start learning other advanced techniques of Machine Learning

How much time does it take to learn Linear regression technique of machine learning?

Linear Regression is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn Linear regression starts from the basics and takes you to advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to remember whatever you have learnt. Therefore, we have also provided you with another data set to work on as a separate project of Linear regression.

What are the steps I should follow to be able to build a Machine Learning model?

You can divide your learning process into 4 parts:

Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part.

Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model

Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the R environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in R

Understanding of Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture in R where we actually run each query with you.


Getting Data Ready for Regression Model

Gathering Business Knowledge

Data Exploration

Course resources

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

Creating 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

Excel: Running Linear Regression using Solver


What-if analysis

Transportation Problem in Excel using Goal Seek

Bonus Section

Bonus Lecture


Mario29 August 2020

I'm have prior experience with linear regression and took this as a refresher. It is an incredible course that shows you important concepts such as preparing the data and methods for dealing with data issues so the inputs to the model improved. I highly recommend the course.

Amrita27 August 2020

Just Ok, am not able to connect the content so far with my intent of this training and objective of this training overall

Clarissa10 August 2020

The material is easy to follow if you are new to Linear Regression Analysis using MS Excel. The instructor gives examples and definitions. I wish he explained better the reasoning for using the numbers 0, 1 for dummy variables. However, it makes sense when he does an example.

José14 July 2020

Es buena materia, pero al final al momento de hablar de regresion lineal simple y multiple fue más lectura de las diapositivas, las cuales igual pueden hacerse de manera manual en excel y no solo la manera directa con la única formula.

Aishwarya9 July 2020

Really informative. I could almost understand everything which I was not able to do so during my college days !!

Vikas22 May 2020

Impressive clarity of thought, with very relevant and to the point explanations. Better than I expected.

Jugkapong21 May 2020

Good course to learn how to use excel's analytic function. This course is good structured and good explained.

Aditya9 May 2020

The course provided great insights. However, it would have been great had the instructor delved into some of the basic of statistics part

Sunday20 April 2020

I like the course from the beginning to the end. I can confidently say the tutor has done a great job.

Aniket18 April 2020

I will recommend this wonderful course to every beginner. It simply well structure course,starting from basic to advance level. Thank You very much Udemy as well as instructor for such nice course.

Md.12 April 2020

It was undoubtedly a wonderful course. The teacher has great experience in this field I must say. I have learned something special which I will implement in my professional life. Thank you Udemy.

Marisol3 April 2020

I don't understand the accent well. It's very distracting form the material and I find myself getting overwhelmed trying to read the caption and slides at the same time

Kashish12 February 2020

Need to talk with more consistency and speed. Overall, the lecture had everything it claimed to have.

Towheedul21 January 2020

The course was so useful and full of resources. I didn't know that regression analysis can be conducted by excel. Many many thanks to the instructor.

Md.25 August 2019

Yes. This course is relevant to my personal research work. I've to collect data myself from field level for my research and hope this research will help me in my upcoming research.


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