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Time Series Forecasting with R: Predict Sales, Demand, and Market Trends Using Modern Data Science Techniques
Paperback
Series: Real-World Data Science with R, Book 20
General ComputersGeneral MathematicsProbability & Statistics
Publisher: Independently Published
Published: Mar 9 2026
Pages: 142
Weight: 0.44
Height: 0.30 Width: 6.00 Depth: 9.00
Language: English
Unlock the Power of Time Series Forecasting with R and Turn Data into Accurate Business Predictions
In today's data-driven world, businesses rely on predictive analytics to make smarter decisions. From forecasting sales and predicting customer demand to identifying market trends and optimizing supply chains, time series forecasting has become a critical skill for data scientists, analysts, and business professionals.
Time Series Forecasting with R is a practical, hands-on guide designed to help you master modern forecasting techniques using the powerful R programming language.
Whether you are a beginner learning data science or a professional analyst seeking advanced forecasting methods, this book walks you step by step through the tools and techniques needed to analyze time-based data and generate accurate predictions.
Inside this book, you will learn how to:
- Understand time series data, trends, seasonality, and patterns
- Explore and visualize time-based datasets using R
- Apply statistical forecasting models including ARIMA and SARIMA
- Build forecasting systems using exponential smoothing techniques
- Implement machine learning approaches for time series prediction
- Forecast sales, demand, inventory, and market trends
- Design a complete forecasting pipeline for real-world business applications
Unlike many theoretical textbooks, this guide focuses on practical applications used by modern businesses and data teams. Each chapter explains concepts clearly while demonstrating how to implement forecasting models directly in R.
By the end of this book, you will be able to:
- Analyze time series datasets confidently
- Build forecasting models that predict future outcomes
- Apply predictive analytics to real-world business problems
- Use R to automate forecasting workflows and data science projects
This book is ideal for:
- Data science students
- Business analysts
- Data analysts and statisticians
- R programmers
- Machine learning practitioners
- Professionals working in finance, marketing, operations, and supply chain
If you want to predict the future using data and build powerful forecasting models with R, this book provides the practical knowledge and tools to get started.
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