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Barsha Saha
In this project, you will learn to conduct a thorough analysis of a time series data using ARIMA. The project explains the basic concepts of time series analysis and illustrates the same with hands-on activity on R Studio. It describes the types of time series data and its distinct components. The project covers how to conduct diagnostic tests to check for core assumptions of ARIMA, evaluating model process and orders from ACF, PACF graphs. Finally, it derives best fit model to forecast future values.
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Syllabus
Project Overview
Welcome to Time Series Analysis (ARIMA) with R. In this guided project, you will learn to conduct a thorough analysis of a time series data using ARIMA. The project explains the basic concepts of time series analysis and illustrates the same with hands-on activity on R Studio. It describes the types of time series data and its distinct components. The project covers how to conduct diagnostic tests to check for core assumptions of ARIMA, evaluating model process and orders from ACF, PACF graphs. Finally, it derives best fit model to forecast future values.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches time series analysis, which is a valuable skill in finance, economics, and other fields
Builds a strong foundation for beginners in time series analysis
Uses R Studio, which is the industry standard for time series analysis
Covers the core concepts of time series analysis, including time series components, stationarity, and ARIMA models
Provides hands-on exercises to reinforce the concepts learned
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Time Series Analysis (ARIMA) with R with these
activities:
Review basic algebra
Show steps
Solidify your understanding of algebraic concepts to prepare for more complex topics in this course
Browse courses on
Algebra
Show steps
-
Review basic algebraic operations, such as addition, subtraction, multiplication, and division
-
Practice solving one-step and two-step equations
-
Simplify algebraic expressions
-
Review solving systems of linear equations
Read 'Time Series Analysis with Applications in R'
Show steps
Sharpen your knowledge and gain a strong foundation for time series analysis through a book
View
Time Series Analysis: With Applications in R...
on Amazon
Show steps
-
Establish a firm grasp of the fundamental concepts of time series analysis
-
Read through theoretical methods and explore their practical applications
-
Enhance your familiarity with statistical concepts and apply them to time series analysis
Participate in a time series analysis study group
Show steps
Engage in discussions and learn from fellow learners
Browse courses on
Time Series Analysis
Show steps
-
Join or start a study group with other students in the course
-
Discuss course concepts and share your understanding
-
Collaborate on solving practice problems and projects
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve time series forecasting problems on LeetCode
Show steps
Strengthen your problem-solving skills in time series forecasting with online practice
Browse courses on
Time Series Forecasting
Show steps
-
Select a variety of time series forecasting problems
-
Practice applying ARIMA models to analyze and forecast real-world time series data
-
Review your solutions and learn from your mistakes
Create a comprehensive study guide
Show steps
Organize and synthesize your notes and materials for effective learning
Show steps
-
Gather all relevant materials, including lecture notes, readings, and practice problems
-
Review and synthesize the materials to create a comprehensive study guide
Develop a curated list of time series analysis resources
Show steps
Create a valuable repository of knowledge for your use and for the benefit of others
Browse courses on
Time Series Analysis
Show steps
-
Identify and gather valuable resources related to time series analysis
-
Organize and curate these resources into a well-structured compilation
Develop a time series forecasting model for a real-world dataset
Show steps
Apply your knowledge to solve a real-world problem using time series forecasting
Browse courses on
Time Series Forecasting
Show steps
-
Choose a business problem that can benefit from time series forecasting
-
Collect and analyze a relevant dataset
-
Build and evaluate an ARIMA model to forecast future values
-
Deploy and monitor your forecasting model to track its performance
Become a mentor for new learners in time series analysis
Show steps
Contribute to the learning community by guiding and supporting others
Browse courses on
Mentoring
Show steps
-
Reach out to new learners or join a mentoring program
-
Share your knowledge and provide guidance to help learners develop their skills
-
Foster a collaborative learning environment
Review basic algebra
Show steps
Solidify your understanding of algebraic concepts to prepare for more complex topics in this course
Browse courses on
Algebra
Show steps
Show steps
Show steps
- Review basic algebraic operations, such as addition, subtraction, multiplication, and division
- Practice solving one-step and two-step equations
- Simplify algebraic expressions
- Review solving systems of linear equations
Read 'Time Series Analysis with Applications in R'
Show steps
Sharpen your knowledge and gain a strong foundation for time series analysis through a book
View
Time Series Analysis: With Applications in R...
on Amazon
Show steps
Show steps
Show steps
- Establish a firm grasp of the fundamental concepts of time series analysis
- Read through theoretical methods and explore their practical applications
- Enhance your familiarity with statistical concepts and apply them to time series analysis
Participate in a time series analysis study group
Show steps
Engage in discussions and learn from fellow learners
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Join or start a study group with other students in the course
- Discuss course concepts and share your understanding
- Collaborate on solving practice problems and projects
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve time series forecasting problems on LeetCode
Show steps
Strengthen your problem-solving skills in time series forecasting with online practice
Browse courses on
Time Series Forecasting
Show steps
Show steps
Show steps
- Select a variety of time series forecasting problems
- Practice applying ARIMA models to analyze and forecast real-world time series data
- Review your solutions and learn from your mistakes
Create a comprehensive study guide
Show steps
Organize and synthesize your notes and materials for effective learning
Show steps
Show steps
Show steps
- Gather all relevant materials, including lecture notes, readings, and practice problems
- Review and synthesize the materials to create a comprehensive study guide
Develop a curated list of time series analysis resources
Show steps
Create a valuable repository of knowledge for your use and for the benefit of others
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Identify and gather valuable resources related to time series analysis
- Organize and curate these resources into a well-structured compilation
Develop a time series forecasting model for a real-world dataset
Show steps
Apply your knowledge to solve a real-world problem using time series forecasting
Browse courses on
Time Series Forecasting
Show steps
Show steps
Show steps
- Choose a business problem that can benefit from time series forecasting
- Collect and analyze a relevant dataset
- Build and evaluate an ARIMA model to forecast future values
- Deploy and monitor your forecasting model to track its performance
Become a mentor for new learners in time series analysis
Show steps
Contribute to the learning community by guiding and supporting others
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Reach out to new learners or join a mentoring program
- Share your knowledge and provide guidance to help learners develop their skills
- Foster a collaborative learning environment
Career center
Learners who complete Time Series Analysis (ARIMA) with R will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts help businesses make better decisions by analyzing data. They use statistical methods to identify trends and patterns in data, and then use that information to make recommendations. This course can help you develop the skills you need to be a successful Data Analyst, including how to collect, clean, and analyze data; how to use statistical methods to identify trends and patterns; and how to communicate your findings to others.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts (or Quants) use mathematical and statistical models to analyze risk and make investment decisions. They play a vital role in the financial industry, and their work can have a significant impact on the bottom line. This course can help you develop the skills you need to become a successful Quant, including how to use statistical methods to model risk and make investment decisions.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make recommendations on investments. They work with companies, individuals, and organizations to help them make informed decisions about their financial future. This course can help you develop the skills you need to become a successful Financial Analyst, including how to analyze financial data, how to make investment recommendations, and how to communicate your findings to others.
Business Analyst
Business Analyst
Business Analysts use data and analysis to help businesses solve problems and make better decisions. They help businesses understand their customers, their processes, and their markets. They can work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to become a successful Business Analyst, including how to collect, clean, and analyze data; how to use statistical methods to identify trends and patterns; and how to communicate your findings to others.
Market Researcher
Market Researcher
Market Researchers collect and analyze data about consumers and markets. They use this information to help businesses understand what their customers want and need, and to help them develop marketing strategies. This course can help you develop the skills you need to become a successful Market Researcher, including how to conduct surveys, how to analyze data, and how to communicate your findings to others.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to help organizations make better decisions. They can work in a variety of industries, including manufacturing, healthcare, and transportation. This course can help you develop the skills you need to become a successful Operations Research Analyst, including how to use statistical methods to model and analyze problems, and how to make recommendations for improvement.
Data Scientist
Data Scientist
Data Scientists use data to solve problems and make better decisions. They use a variety of techniques, including statistical modeling, machine learning, and data mining. This course can help you develop the skills you need to become a successful Data Scientist, including how to collect, clean, and analyze data; how to use statistical methods to identify trends and patterns; and how to build and deploy predictive models.
Statistician
Statistician
Statisticians use data to solve problems and make better decisions. They use a variety of statistical methods to analyze data and make inferences. This course can help you develop the skills you need to become a successful Statistician, including how to collect, clean, and analyze data; how to use statistical methods to identify trends and patterns; and how to communicate your findings to others.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and make financial decisions. They work in a variety of industries, including insurance, finance, and healthcare. This course can help you develop the skills you need to become a successful Actuary, including how to use statistical methods to model risk and make financial decisions.
Economist
Economist
Economists use economic theories and data to analyze and make recommendations on economic policies. They work in a variety of settings, including government, academia, and business. This course can help you develop the skills you need to become a successful Economist, including how to use statistical methods to analyze economic data.
Epidemiology
Epidemiology
Epidemiologists study the distribution and determinants of health-related events in populations. They use this information to develop and evaluate public health interventions. This course can help you develop the skills you need to become a successful Epidemiologist, including how to use statistical methods to analyze health data.
Operational Risk Manager
Operational Risk Manager
Operational Risk Managers identify, assess, and manage risks that could disrupt a company's operations. They work in a variety of industries, including financial services, healthcare, and manufacturing. This course can help you develop the skills you need to become a successful Operational Risk Manager, including how to use statistical methods to identify and assess risks.
Portfolio Manager
Portfolio Manager
Portfolio Managers make investment decisions for their clients. They work in a variety of settings, including banks, investment firms, and hedge funds. This course can help you develop the skills you need to become a successful Portfolio Manager, including how to use statistical methods to analyze investment data.
Risk Manager
Risk Manager
Risk Managers identify, assess, and manage risks that could impact a company's financial performance. They work in a variety of industries, including banking, insurance, and manufacturing. This course can help you develop the skills you need to become a successful Risk Manager, including how to use statistical methods to identify and assess risks.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks that could impact a company's profitability or reputation. They work in a variety of industries, including financial services, healthcare, and manufacturing. This course can help you develop the skills you need to become a successful Risk Analyst, including how to use statistical methods to identify and assess risks.
For more career information including salaries, visit:
OpenCourser.com/course/eo8sys/time
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Time Series Analysis (ARIMA) with R.
Save
Provides a comprehensive introduction to time series econometrics, with a focus on applications in economics and finance. It valuable resource for students and practitioners in economics and finance.
Provides a comprehensive introduction to time series analysis using R, with a focus on practical applications in data science and machine learning. It is written in a clear and accessible style, making it a good choice for both students and practitioners.
Save
Provides a comprehensive introduction to time series analysis, covering both the theoretical foundations and practical modeling techniques. It is written in a clear and accessible style, making it a good choice for both students and practitioners.
Save
This classic textbook provides a comprehensive introduction to time series analysis, covering both the theoretical foundations and practical modeling techniques. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to time series analysis, covering both the theoretical foundations and practical modeling techniques. It is written in a clear and accessible style, making it a good choice for both students and practitioners.
Save
This textbook provides a practical guide to time series analysis, with a focus on applications in forecasting and modeling. It is written in a clear and accessible style, making it a good choice for both students and practitioners.
Provides a comprehensive introduction to time series analysis and prediction, with a focus on theoretical foundations and mathematical techniques. It valuable resource for students and researchers in mathematics, statistics, and computer science.
Provides a practical guide to time series analysis, with a focus on applications in social sciences and business. It is written in a clear and accessible style, making it a good choice for students and practitioners with little or no prior knowledge of time series analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/eo8sys/time
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Effort
2 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Barsha Saha
Language
English
Good to know
Teaches time series analysis, which is a valuable skill in finance, economics, and other fields
Builds a strong foundation for beginners in time series analysis
Uses R Studio, which is the industry standard for time series analysis
Covers the core concepts of time series analysis, including time series components, stationarity, and ARIMA models
Provides hands-on exercises to reinforce the concepts learned
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