Offer ends in:
What you'll get
- 4+ Hours
- 1 Courses
- Course Completion Certificates
- One year access
- Self-paced Courses
- Technical Support
- Mobile App Access
- Case Studies
Synopsis
- Methods of Forecasting and Steps in Forecasting
- Problems in Forecasting and Simple Forecasting Methods
- Simple and Multiple Regression and Time Series Decomposition
- Exponential Smoothing and ARIMA models
Content
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MODULE 1: Essentials Training
Courses No. of Hours Certificates Details Time Series Analysis and Forecasting using R 4h 34m ✔
Description
About Time Series Analysis and Forecasting using R
Learn how to effectively work around business analytics to find out answers to key questions related to business. We are using sophisticated statistical tools like R and excel to analyze data. This training is a practical and a quantitative course which will help you learn business analytics with the perspective of a data scientist. The learner of this course will learn the most relevant techniques used in the real world by data analysts of companies around the world.
The training includes the following;
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Introduction to Forecasting
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Models/Methods of Forecasting
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Steps in Forecasting
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Problems in Forecasting
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Simple Forecasting Methods
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Simple and Multiple Regression
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Time Series Decomposition
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Exponential Smoothing
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ARIMA models
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Conclusion
Time series in R is defined as a series of values, each associated with the timestamp also measured over regular intervals (monthly, daily) like weather forecasting and sales analysis. The R stores the time series data in the time-series object and is created using the ts() function as a base distribution.
How Time-series works in R?
R has a powerful inbuilt package to analyze the time series or forecasting. Here it builds a function to take different elements in the process. At last, we should find a better fit for the data. The input data we use here are integer values. Not all data has time values, but their values could be made as time-series data. The data consists of observations over a regular interval of time. It needs several transformations before it is modeled up.
Requirements
- Basic knowledge in statistics, mathematics, programming
- Basic knowledge of using R and Excel
Target Audience
- Students, Marketing professionals, Market Researchers, Product Managers, Any person running a business
Course Ratings
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This tutorial was really helpful in understanding forecasting using R. The explanation was really easy to understand and the examples were really useful. The coverage of topics was good starting with the basics then going deep into the topics. they have covered simple forecasting methods, transformations, and adjustments, time series regressions and arima models
SHUSHANTH T
A very well explained Course. The lucid way of explaining helps clarify several issues. The complex issues like multiple regression are covered in an easy to understand manner. Real-life examples are used very well in each technique. Makes application to industry-specific cases easier. Audio explanations are very good.
INDER SETHI