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Key benefits

Segment data, regression predictions, and time series forecasts without writing any code

Group multiple variables with K-means using Excel plugin without programming

Build, validate, and predict with a multiple linear regression model and time series forecasts

Description

Data Forecasting and Segmentation Using Microsoft Excel guides you through basic statistics to test whether your data can be used to perform regression predictions and time series forecasts. The exercises covered in this book use real-life data from Kaggle, such as demand for seasonal air tickets and credit card fraud detection. You’ll learn how to apply the grouping K-means algorithm, which helps you find segments of your data that are impossible to see with other analyses, such as business intelligence (BI) and pivot analysis. By analyzing groups returned by K-means, you’ll be able to detect outliers that could indicate possible fraud or a bad function in network packets. By the end of this Microsoft Excel book, you’ll be able to use the classification algorithm to group data with different variables. You’ll also be able to train linear and time series models to perform predictions and forecasts based on past data.

What you will learn

Understand why machine learning is important for classifying data segmentation

Focus on basic statistics tests for regression variable dependency

Test time series autocorrelation to build a useful forecast

Use Excel add-ins to run K-means without programming

Analyze segment outliers for possible data anomalies and fraud

Build, train, and validate multiple regression models and time series forecasts

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Exploring Microsoft Excel's Hidden Treasures

€19.99

Hands-On Financial Modeling with Excel for Microsoft 365

€27.99

Data Forecasting and Segmentation Using Microsoft Excel

€35.99

Total € 83.97

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Amazon verified reviews

Albert Bellamy Jun 03, 2022

The writing style is expository. It’s descriptive and no-nonsense. The author does a wonderful job of talking through the concepts at first, then going into techniques.Figures and examples are very good for showing the work, and the author clearly knows his subject material.The biggest revelation in this book was my discovery of BERT, a 3rd party add-in that enables the user to code in R while using Excel. R is my favorite language, and I find it much more useful than VBA. So to be able to create data structures in R and apply them to Excel was invaluable.Each chapter ends with a check on learning quiz of 2-5 questions. These are mostly fill in the blank type questions, and the answers are immediately below the questions, which is a bit annoying.In the preface, the author says this:If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository.The book is written in such a way that you can follow along with the procedures. Tough it out through the first 4 chapters, which are a review of key statistical concepts. You’ll get to chapter 5 before you start doing any work. But once you get going, it’s good.Some of the instructions are not easy to follow, and this is why it's not a perfect book. Getting going with BERT was challenging for me, and the step-by-step instructions at first are not great.Slight missed opportunity: The Excel files function mostly as a check on learning. They are not built to enable progressive learning, just to show the end result. They’re not much more useful than the pictures in the text. This also could have been a better vehicle for troubleshooting and development of the learner.One item of minor annoyance: the English isn’t great. Neither the author nor the two editors are native English speakers, and it shows. There are quite a few examples of clunky language or typos that should have been caught with a proper edit.All in all, a very good book. I recommend it for anyone who is at least proficient in Excel and wants a great guide on time series analysis, advanced models and superior visualization capabilities in Excel.

Amazon Verified review

Daksh Aug 06, 2022

Loved the book, did not realize how powerful MS Excel was untill I found this book. I had never used plugin before but knowing thats its widely available and have improved so much in last few years I think everyone should give it a try.This books help in making our life easier.I am a Masters student and in all my course I have just used excel to store the data, used Python or R for analysis and Tableau and Power BI for Visualization. But having the knowledge this books gives enhances our way of working in a company or for our own business on Excel even without any knowledge of R or Python.I highly recommend this book for beginners and also people using Excel in thier Businesses.

Vandita Bothra Jun 12, 2022

Data forecasting and segmentation using Microsoft Excel is a great book for someone who wants to get a foothold in the analytics world. The explanation and language used is simple and clear to understand some fairly complex models to not overwhelm the reader. The author has provided the theoretical knowledge to understand the models and supplemented it with practical examples in excel and taken a step further by providing R libraries and code for the same.It explains very well the distinction between supervised and unsupervised learning and the important models used in each category.This book covers 3 very important and most frequently used models at work- Segmentation, Regression and Time series forecasting. My latest project at work requires time series forecasting and this book helped to brush my basics and kept the steps clear in my mind to chart out the timeline.The quick QnA session post the summary was a nice way for the content to stick but the further reading resource is a great addition for someone to dig deeper!

Rini Mukherjee Jun 01, 2022

- The book is an excellent start for understanding the basics of statistics and regression analysis, and its relation to processing, modelling and using machine learning data- One of the best features of the book are Key questions and answers at the end of the chapter summary. This allows the reader to test their learning as well as increase knowledge on go to questions related to statistical analysis-The technical link to the real world data and to be able to work with the different variables, data sets, the codes, syntax and pivot tables make it very well rounded for the reader who can practically work with the data and get into the weeds of it- Additionally, if there were some interactive assignments at the end of each chapter would help readers to solve some of the problems by themselves and have a higher level of understanding on the subject

Shailesh Patel Jul 14, 2022

- This book is for beginners to understand the basics of statistical analysis using Excel.- Best of this book is that the are some assignments after each chapter, which are useful to understand and solve readers' queries. - Overall, a good book to understand time series analysis, advanced modeling, and visualization in Excel

Data Forecasting and Segmentation Using Microsoft Excel: Perform data grouping, linear predictions, and time series machine learning statistics without using code

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