Time Series Analysis (ARIMA) with R faq

instructor Instructor: Barsha Saha instructor-icon
duration Duration: duration-icon

This project is perfect for anyone interested in learning the fundamentals of time series analysis using ARIMA. Through this project, you will gain a comprehensive understanding of the concepts of time series analysis and its application in R Studio. You will learn to identify the components of time series data, conduct diagnostic tests, and evaluate model process and orders. Finally, you will be able to forecast future values with the best fit model.

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Paid

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

29th May, 2023

Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 31st, 2023]

Skills and Knowledge:
- Understanding of time series analysis and its components
- Knowledge of ARIMA models and their assumptions
- Ability to diagnose and evaluate time series data
- Ability to identify and select the best fit ARIMA model
- Ability to forecast future values using ARIMA models
- Proficiency in using R Studio for time series analysis

Professional Growth:
This course on Time Series Analysis (ARIMA) with R contributes to professional growth in several ways:
1. Enhanced analytical skills: By learning how to conduct a thorough analysis of time series data using ARIMA, professionals can develop their analytical skills. They will gain a deeper understanding of time series data and its distinct components, allowing them to make more informed decisions and predictions based on historical patterns.
2. Proficiency in R programming: The course provides hands-on activities using R Studio, which helps professionals develop proficiency in R programming. R is a widely used programming language for statistical analysis and data visualization, and being proficient in R can open up new opportunities for professionals in various industries.
3. Understanding diagnostic tests: The course covers how to conduct diagnostic tests to check for core assumptions of ARIMA models. This knowledge is crucial for professionals working with time series data, as it helps them ensure the accuracy and reliability of their models. Understanding diagnostic tests also allows professionals to identify and address any issues or anomalies in the data.
4. Model evaluation and selection: The course teaches professionals how to evaluate the model process and determine the orders from ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) graphs. This skill is essential for selecting the best-fit model for forecasting future values. By mastering model evaluation and selection techniques, professionals can improve the accuracy of their predictions and make more effective business decisions.
5. Forecasting future values: The course concludes by teaching professionals how to derive the best-fit model to forecast future values. This skill is valuable in various industries, such as finance, sales, and supply chain management, where accurate forecasting can help optimize resource allocation, inventory management, and financial planning.
Overall, this course equips professionals with the knowledge and skills necessary to analyze time series data, build accurate models, and make informed predictions. This can significantly contribute to their professional growth by enhancing their analytical abilities, programming skills, and decision-making capabilities.

Further Education:
This course on Time Series Analysis (ARIMA) with R is suitable for preparing for further education. It covers the basic concepts of time series analysis and provides hands-on activities using R Studio. It also teaches how to conduct diagnostic tests and evaluate model processes and orders. Additionally, it focuses on deriving the best fit model for forecasting future values. These skills and knowledge are valuable for further education in fields such as economics, finance, statistics, and data science.

Course Provider

Provider Coursera's Stats at AZClass

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faq FAQ for Time Series Analysis Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a paid certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

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