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Dr Prashan S. M. Karunaratne
This course allows learners to explore Regression Models in order to utilise these models for business forecasting. Unlike Time Series Models, Regression Models are causal models, where we identify certain variables in our business that influence other variables. Regressions model this causality, and then we can use these models in order to forecast, and then plan for our business' needs. We will explore simple regression models, multiple regression models, dummy variable regressions, seasonal variable regressions, as well as autoregressions. Each of these are different forms of regression models, tailored to unique business scenarios, in order to forecast and generate business intelligence for organisations.
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What's inside
Syllabus
Welcome and Critical Information
Regression Models
In this module, we explore the context and purpose of business forecasting and the three types of business forecasting using regression models. We will learn the theoretical underpinning for a regression model, and understand the relationship between explanatory variables and dependent variables. We will first focus on single variable or simple regression, and learn how to critically evaluate the model using regression diagnostic tools and then use our models for forecasting to suit our organisation's needs.
Read more
Syllabus
Welcome and Critical Information
Regression Models
In this module, we explore the context and purpose of business forecasting and the three types of business forecasting using regression models. We will learn the theoretical underpinning for a regression model, and understand the relationship between explanatory variables and dependent variables. We will first focus on single variable or simple regression, and learn how to critically evaluate the model using regression diagnostic tools and then use our models for forecasting to suit our organisation's needs.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Explores regression models, which is standard in business forecasting
Teaches skills, knowledge, and tools that are highly relevant to industry
Develops skills and knowledge that are core for business forecasting
Taught by Dr Prashan S. M. Karunaratne, who is recognized for their work in business forecasting
Provides hands-on labs and interactive materials
Requires learners to come in with some background knowledge
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Reviews summary
Excel regression for business forecasting
According to learners, this course is a highly practical and accessible introduction to using Excel for business forecasting. Students generally find the course provides a solid foundation in various regression models, including simple, multiple, and dummy variable regressions, with a strong focus on their real-world business application. Many praise the clear explanations and hands-on approach, making complex topics understandable. While largely positive, some more statistically-inclined learners suggest the theoretical depth could be enhanced, indicating it's geared towards practical application rather than deep statistical rigor. Overall, it's considered effective for professionals seeking to apply forecasting techniques directly.
Generally well-paced, but some modules felt condensed.
"The course flow was logical and progressive, building concepts effectively from simple to more complex models."
"I found the initial modules well-paced, but some advanced topics like autoregression seemed to be covered too quickly."
"Sometimes the pace picked up considerably in later sections, requiring me to rewatch certain lectures for full understanding."
Provides a comprehensive base for various forecasting methods.
"This course laid a very solid foundation for understanding and applying various regression models for forecasting."
"I gained a comprehensive overview of simple, multiple, and dummy variable regressions relevant to business scenarios."
"It serves as an excellent starting point for anyone looking to incorporate forecasting into their business analysis."
Complex regression concepts are made highly understandable.
"The instructor did an excellent job of breaking down complex regression topics into digestible parts."
"I appreciated the clear, step-by-step guidance, especially on the diagnostic tools used for model evaluation."
"Even as someone relatively new to regression, I found the explanations very easy to follow and apply."
Excellent for applying regression models directly in Excel.
"I found the ability to apply these models directly in Excel for business data incredibly practical."
"The course excels at showing you how to implement forecasting techniques using everyday Excel, which was my primary goal."
"I now feel confident using Excel for regression analysis for my business forecasting needs after completing this course."
Some learners desire more statistical theory depth.
"While great for practical application, I hoped for a bit more depth on the underlying statistical theory."
"For those with a stronger statistical background, the theoretical explanations might feel somewhat limited."
"I would have liked a deeper dive into the mathematical derivations behind some of the concepts presented."
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 Excel Regression Models for Business Forecasting with these
activities:
Read 'Regression Analysis for Forecasting' by Gareth James et al.
Show steps
Gain a comprehensive understanding of regression models for forecasting by reviewing 'Regression Analysis for Forecasting', a well-regarded text in the field.
View
An Introduction to Statistical Learning
on Amazon
Show steps
-
Purchase or borrow the book
-
Read the chapters relevant to the course curriculum
-
Highlight and take notes on key concepts
Connect with a Regression Model Expert
Show steps
Seek guidance from an experienced professional in the field to enhance your learning journey and gain valuable insights.
Browse courses on
Regression Models
Show steps
-
Identify potential mentors through online platforms or professional networks
-
Reach out to your preferred mentors and express your interest
-
Schedule a meeting or call to discuss your learning goals and expectations
-
Regularly communicate with your mentor and seek their advice
Solve Regression Model Exercises
Show steps
Enhance your understanding of regression models by solving a variety of practice exercises.
Browse courses on
Regression Models
Show steps
-
Identify online platforms or textbooks with regression model exercises
-
Practice solving a range of regression model exercises
-
Review your answers and identify areas for improvement
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Case Studies on Regression Model Application
Show steps
Gain insights into practical applications of regression models by exploring real-world case studies from various industries.
Browse courses on
Regression Models
Show steps
-
Identify industries or domains of interest
-
Search for case studies related to regression model applications
-
Analyze the case studies to understand the context and problem
-
Extract key learnings and best practices
Attend a Regression Model Workshop or Conference
Show steps
Network with experts, learn about the latest advancements, and enhance your practical skills by participating in a regression model workshop or conference.
Browse courses on
Regression Models
Show steps
-
Research upcoming regression model workshops or conferences
-
Register for the event
-
Attend the sessions and actively participate in discussions
-
Connect with other attendees and experts in the field
Forecast Business Using Regression Models
Show steps
Develop a practical understanding of utilizing regression models for forecasting and planning by carrying out a hands-on business forecasting project.
Browse courses on
Regression Models
Show steps
-
Gather Data Relevant to the Forecasting Problem
-
Select and Prepare Appropriate Explanatory Variables
-
Build and Evaluate a Regression Model
-
Forecast Future Values of the Dependent Variable
-
Interpret and Analyze the Forecast Results
Develop a Regression Model Tutorial
Show steps
Reinforce your grasp of regression models by creating a comprehensive tutorial that explains the concepts in a clear and engaging manner.
Browse courses on
Regression Models
Show steps
-
Choose a specific aspect of regression models to focus on
-
Develop a structured outline for the tutorial
-
Write the tutorial content, ensuring clarity and accuracy
-
Proofread and refine the tutorial
Contribute to Open-Source Regression Model Implementations
Show steps
Gain practical experience in implementing regression models and contribute to the open-source community.
Browse courses on
Regression Models
Show steps
-
Identify open-source projects related to regression models
-
Select a project to contribute to
-
Understand the project's codebase and documentation
-
Implement new features or enhancements to the regression model
-
Submit a pull request with your contributions
Read 'Regression Analysis for Forecasting' by Gareth James et al.
Show steps
Gain a comprehensive understanding of regression models for forecasting by reviewing 'Regression Analysis for Forecasting', a well-regarded text in the field.
View
An Introduction to Statistical Learning
on Amazon
Show steps
Show steps
Show steps
- Purchase or borrow the book
- Read the chapters relevant to the course curriculum
- Highlight and take notes on key concepts
Connect with a Regression Model Expert
Show steps
Seek guidance from an experienced professional in the field to enhance your learning journey and gain valuable insights.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Identify potential mentors through online platforms or professional networks
- Reach out to your preferred mentors and express your interest
- Schedule a meeting or call to discuss your learning goals and expectations
- Regularly communicate with your mentor and seek their advice
Solve Regression Model Exercises
Show steps
Enhance your understanding of regression models by solving a variety of practice exercises.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Identify online platforms or textbooks with regression model exercises
- Practice solving a range of regression model exercises
- Review your answers and identify areas for improvement
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Case Studies on Regression Model Application
Show steps
Gain insights into practical applications of regression models by exploring real-world case studies from various industries.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Identify industries or domains of interest
- Search for case studies related to regression model applications
- Analyze the case studies to understand the context and problem
- Extract key learnings and best practices
Attend a Regression Model Workshop or Conference
Show steps
Network with experts, learn about the latest advancements, and enhance your practical skills by participating in a regression model workshop or conference.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Research upcoming regression model workshops or conferences
- Register for the event
- Attend the sessions and actively participate in discussions
- Connect with other attendees and experts in the field
Forecast Business Using Regression Models
Show steps
Develop a practical understanding of utilizing regression models for forecasting and planning by carrying out a hands-on business forecasting project.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Gather Data Relevant to the Forecasting Problem
- Select and Prepare Appropriate Explanatory Variables
- Build and Evaluate a Regression Model
- Forecast Future Values of the Dependent Variable
- Interpret and Analyze the Forecast Results
Develop a Regression Model Tutorial
Show steps
Reinforce your grasp of regression models by creating a comprehensive tutorial that explains the concepts in a clear and engaging manner.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Choose a specific aspect of regression models to focus on
- Develop a structured outline for the tutorial
- Write the tutorial content, ensuring clarity and accuracy
- Proofread and refine the tutorial
Contribute to Open-Source Regression Model Implementations
Show steps
Gain practical experience in implementing regression models and contribute to the open-source community.
Browse courses on
Regression Models
Show steps
Show steps
Show steps
- Identify open-source projects related to regression models
- Select a project to contribute to
- Understand the project's codebase and documentation
- Implement new features or enhancements to the regression model
- Submit a pull request with your contributions
Career center
Learners who complete Excel Regression Models for Business Forecasting will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment recommendations. To be successful in this role, it is crucial to have a strong understanding of data analysis techniques. This course explores regression models, a fundamental technique for analyzing financial data and forecasting trends.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems and make predictions. To be successful in this role, it is critical to have a strong foundation in data analysis and modeling techniques. This course explores regression models, a key technique for data analysis and forecasting, which may be useful for your work as a Data Scientist.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data. To be successful in this role, it is critical to have a strong foundation in data analysis techniques. This course explores regression models, a key data analysis technique, and how they can be used to make forecasts.
Actuary
Actuary
An Actuary assesses financial risks and develops strategies to mitigate those risks. To be successful in this role, it is critical to have a strong foundation in data analysis techniques. This course explores regression models, a key data analysis technique for evaluating and forecasting risks.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models to solve business problems. To be successful in this role, it is critical to have a strong foundation in data analysis and modeling techniques. This course explores regression models, a key technique for data analysis and forecasting, which may be useful for your work as a Machine Learning Engineer.
Business Analyst
Business Analyst
A Business Analyst identifies and solves problems within a business, examining how a business operates and making recommendations for improvements. As a Business Analyst, you will likely need to be able to analyze data and make recommendations for change. This course can help build a foundation in data analysis techniques, as well as in making recommendations based on data.
Data Analyst
Data Analyst
A Data Analyst studies and interprets data to help businesses understand their customers and make better decisions. To be successful in this role, it is helpful to have a strong foundation in data analysis techniques. This course provides a foundation in regression models, a useful technique for data analysis.
Financial Analyst
Financial Analyst
A Financial Analyst helps businesses make financial decisions by investigating and interpreting financial data. To be successful as a Financial Analyst, you may need to be able to understand and use a variety of data analysis techniques. This course provides an introduction to regression models and explores how those models can be used to make forecasts. This is a skill that may be useful for your work as a Financial Analyst.
Consultant
Consultant
A Consultant provides expert advice to organizations on various topics. To be successful in this role, it is important to be able to analyze data and provide insights. This course explores regression models, a powerful tool for analyzing data and making forecasts, which could be a valuable skill for a Consultant.
Market Researcher
Market Researcher
A Market Researcher studies market trends and customer behavior to help businesses make informed decisions. To be successful in this role, it is essential to be able to analyze data and make recommendations based on that data. This course introduces key data analysis techniques, including regression models, which may be useful for your work as a Market Researcher.
Risk Manager
Risk Manager
A Risk Manager identifies, analyzes, and mitigates risks for an organization. To be successful in this role, it is important to have a strong foundation in data analysis techniques. This course provides an introduction to regression models, a helpful tool for analyzing data and making forecasts.
Operations Manager
Operations Manager
An Operations Manager oversees the day-to-day operations of a business. To be successful in this role, it is helpful to have a strong foundation in data analysis. This course explores regression models, a powerful tool for data analysis, and how those models can be used to make forecasts.
Sales Manager
Sales Manager
A Sales Manager leads and motivates a sales team to achieve sales targets. To be successful in this role, it is often helpful to have a strong understanding of data analysis techniques. This course explores regression models, a key technique for data analysis, and how they can be used to make forecasts, which could be a useful skill for a Sales Manager.
Marketing Manager
Marketing Manager
A Marketing Manager develops and executes marketing campaigns to promote a product or service. To be successful in this role, it is important to be able to understand and interpret data. This course introduces regression models, an important data analysis technique for making forecasts, which may be useful in this role.
Project Manager
Project Manager
A Project Manager plans, organizes, and manages projects from start to finish. To be successful, Project Managers often need to be able to analyze data and make decisions based on that data. This course may be useful for learning how to use regression models, a key data analysis technique, to make forecasts.
For more career information including salaries, visit:
OpenCourser.com/course/e98fqh/excel
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
Excel Regression Models for Business Forecasting.
Provides a comprehensive overview of multiple regression, including discussions of data preparation, model fitting, and model diagnostics. It valuable resource for those who want to learn more about the theory and practice of multiple regression.
Provides a comprehensive overview of causal inference, including discussions of regression models for causal inference. It valuable resource for those who want to learn more about the theory and practice of causal inference.
Save
Provides a comprehensive overview of business forecasting, including discussions of regression models for business forecasting. It valuable resource for those who want to learn more about the theory and practice of business forecasting.
Save
Provides a comprehensive overview of forecasting, including discussions of regression models for forecasting. It valuable resource for those who want to learn more about the theory and practice of forecasting.
Save
Provides a comprehensive overview of statistical methods for forecasting, including discussions of regression models for forecasting. It valuable resource for those who want to learn more about the theory and practice of statistical methods for forecasting.
Provides a comprehensive overview of regression modeling with actuarial and financial applications, including discussions of regression models for forecasting. It valuable resource for those who want to learn more about the theory and practice of regression modeling with actuarial and financial applications.
Provides a comprehensive overview of generalized linear models, including discussions of regression models for forecasting. It valuable resource for those who want to learn more about the theory and practice of generalized linear models.
Provides a comprehensive overview of forecasting methods and applications, including discussions of regression models for forecasting. It valuable resource for those who want to learn more about the theory and practice of forecasting methods and applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/e98fqh/excel
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Macquarie University
Instructor
Dr Prashan S. M. Karunaratne
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This course belongs to a
collection
called
Excel Skills for Business Forecasting. It's comprised of three courses:
- Excel Time Series Models for Business Forecasting
- Judgmental Business Forecasting in Excel
- Excel Regression Models for Business Forecasting (viewing)
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