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Tricia Bagley
There are many times when having a crystal ball might be useful and it’s natural to leverage trusted predictions of future outcomes to prepare for the future and make strategic decisions. Predicting Performance is especially key to decision-making and risk...
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There are many times when having a crystal ball might be useful and it’s natural to leverage trusted predictions of future outcomes to prepare for the future and make strategic decisions. Predicting Performance is especially key to decision-making and risk management. In this project, you will build prediction skills with Moving Averages or MA. MA is classic method of time series decomposition most often used with financial predictions. As you work with MA you will also learn how to evaluate and choose the highest performing model to make the most accurate predictions. You will build your skill as we work side-by-side in the free-to-use software Google Sheets. By the end of this project, you will understand use cases for conducting MA trend forecasts in your workplace, be able to conduct MA forecasting in any spreadsheet software, and be able to confidently select the best performing forecast model to enable decision-making. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for beginners seeking a foundation in time series decomposition
Ideal for individuals in finance or economics who require forecasting skills
Assumes familiarity with spreadsheet software like Google Sheets
Focuses primarily on Moving Averages for forecasting, not exploring other techniques

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Reviews summary

Forecasting in google sheets

This course teaches you how to use Moving Averages (MA) to predict performance in Google Sheets. You'll learn how to evaluate and choose the highest performing model to make the most accurate predictions.

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 Predict Performance Using MA Forecasting in Google Sheets with these activities:
Review foundational statistics concepts
Refresh foundational statistics concepts to provide a strong foundation for the course materials.
Browse courses on Statistics
Show steps
  • Review basic probability
  • Review statistical inference
  • Review regression analysis
Review time series analysis techniques
Before beginning the course, students will greatly benefit by reviewing time series analysis techniques as a prerequisite.
Browse courses on Time Series Analysis
Show steps
  • Review ARIMA
  • Review SARIMA
  • Review ETS
  • Review Prophet
Attend a webinar on time series forecasting
Consume an online webinar on time series forecasting to supplement the course's materials and expand knowledge.
Browse courses on Time Series Forecasting
Show steps
  • Register for a webinar
  • Attend the webinar
  • Take notes and engage
Five other activities
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Show all eight activities
Practice creating moving averages in Google Sheets
Practice working with moving averages in Google Sheets to reinforce MA forecasting techniques.
Browse courses on Moving Averages
Show steps
  • Create a moving average using a formula
  • Create a moving average using a function
  • Evaluate and compare the results
Compile a resource list of time series analysis tools
Compile a resource list on time series analysis tools to synthesize and expand on the course's materials.
Browse courses on Time Series Analysis
Show steps
  • Research time series analysis tools
  • Evaluate and compare tools
  • Create a resource list
Build a dashboard to visualize MA forecasts
Complete a project that reinforces dashboarding techniques taught in the course as they apply to time series analysis.
Browse courses on Data Visualization
Show steps
  • Gather data and prepare visualizations
  • Create interactive visualizations
  • Deploy the dashboard
Participate in a time series forecasting competition
Apply time series forecasting skills in a competitive setting to test and refine knowledge.
Browse courses on Time Series Forecasting
Show steps
  • Find a suitable competition
  • Prepare data and models
  • Submit results and analyze performance
Contribute to an open-source time series forecasting library
Engage with the time series forecasting community by contributing to an open-source library.
Browse courses on Time Series Forecasting
Show steps
  • Find a suitable project
  • Contribute code or documentation
  • Engage with the community

Career center

Learners who complete Predict Performance Using MA Forecasting in Google Sheets will develop knowledge and skills that may be useful to these careers:
Financial Analyst
Financial Analysts create financial models to predict future performance, both for companies and for the market as a whole. Because so much of their work is based on making accurate predictions, Financial Analysts can greatly benefit from learning how to build and utilize effective time series forecasting models using Moving Averages in Google Sheets. This course provides a perfect primer for those who wish to become Financial Analysts, with a particular emphasis on model building and selection for performance prediction.
Actuary
Actuaries are responsible for assessing and managing financial risk. This often includes using time series forecasting models to predict future cash flows, claims, and other financial outcomes. Learning how to build and use Moving Average forecasting models in Google Sheets can be a helpful tool in performing these duties. This course can help Actuaries develop the skills they need to build accurate and reliable forecasting models to support their risk management work.
Data Analyst
Data Analysts use data to solve business problems and make better decisions. This often involves using time series forecasting models to predict future trends and outcomes. Moving Average models are a popular forecasting technique that can be easily implemented in Google Sheets. This course can help Data Analysts learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Data Analysts who want to improve their forecasting accuracy and make better data-driven decisions.
Market Researcher
Market Researchers study market trends to help businesses understand their customers and make better decisions. This often involves using time series forecasting models to predict future demand and sales. Moving Average models are a simple and effective forecasting technique that can be used to predict future market trends. This course can help Market Researchers learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Market Researchers who want to improve their forecasting accuracy and make better data-driven decisions.
Portfolio Manager
Portfolio Managers manage investments for individuals and institutions. This often involves using time series forecasting models to predict future market trends and returns. Moving Average models are a popular forecasting technique that can be used to predict future financial outcomes. This course can help Portfolio Managers learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Portfolio Managers who want to improve their forecasting accuracy and make better investment decisions.
Financial Planner
Financial Planners help individuals and businesses plan for their financial future. This often involves using time series forecasting models to predict future income, expenses, and investments. Moving Average models are a simple and effective forecasting technique that can be used to predict future financial outcomes. This course can help Financial Planners learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Financial Planners who want to improve their forecasting accuracy and make better data-driven financial plans for their clients.
Business Analyst
Business Analysts use data to identify and solve business problems. This often involves using time series forecasting models to predict future performance and outcomes. Moving Average models are a popular forecasting technique that can be easily implemented in Google Sheets. This course can help Business Analysts learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Business Analysts who want to improve their forecasting accuracy and make better data-driven decisions.
Investment Analyst
Investment Analysts evaluate and recommend investments for individuals and institutions. This often involves using time series forecasting models to predict future stock prices and market trends. Moving Average models are a popular forecasting technique that can be used to predict future financial outcomes. This course can help Investment Analysts learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Investment Analysts who want to improve their forecasting accuracy and make better investment decisions.
Risk Manager
Risk Managers assess and manage financial risk for businesses and organizations. This often involves using time series forecasting models to predict future financial outcomes and risks. Moving Average models are a popular forecasting technique that can be used to predict future financial outcomes. This course can help Risk Managers learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Risk Managers who want to improve their forecasting accuracy and make better risk management decisions.
Statistician
Statisticians use data to solve problems and make better decisions. This often involves using time series forecasting models to predict future outcomes and trends. Moving Average models are a popular forecasting technique that can be used to predict future outcomes. This course can help Statisticians learn how to build and use Moving Average forecasting models in Google Sheets. This can be a valuable skill for Statisticians who want to improve their forecasting accuracy and make better data-driven decisions.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This often involves using time series forecasting models to predict future stock prices and market trends. Moving Average models are a popular forecasting technique that can be used to predict future financial outcomes. This course may be useful for Quantitative Analysts who want to learn how to build and use Moving Average forecasting models in Google Sheets. This can be a helpful skill for Quantitative Analysts who want to improve their forecasting accuracy and make better investment decisions.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve business problems. This often involves using time series forecasting models to predict future demand, supply, and other operational metrics. Moving Average models are a popular forecasting technique that can be used to predict future operational outcomes. This course may be useful for Operations Research Analysts who want to learn how to build and use Moving Average forecasting models in Google Sheets. This can be a helpful skill for Operations Research Analysts who want to improve their forecasting accuracy and make better data-driven decisions.
Economist
Economists study the economy and make predictions about future economic trends. This often involves using time series forecasting models to predict future economic growth, inflation, and other economic indicators. Moving Average models are a popular forecasting technique that can be used to predict future economic outcomes. This course may be useful for Economists who want to learn how to build and use Moving Average forecasting models in Google Sheets. This can be a helpful skill for Economists who want to improve their forecasting accuracy and make better economic predictions.
Data Scientist
Data Scientists use data to solve problems and make better decisions. This often involves using time series forecasting models to predict future outcomes and trends. Moving Average models are a popular forecasting technique that can be used to predict future outcomes. This course may be useful for Data Scientists who want to learn how to build and use Moving Average forecasting models in Google Sheets. This can be a helpful skill for Data Scientists who want to improve their forecasting accuracy and make better data-driven decisions.
Software Engineer
Software Engineers design, develop, and maintain software applications. This often involves using time series forecasting models to predict future software usage and performance. Moving Average models are a popular forecasting technique that can be used to predict future software outcomes. This course may be useful for Software Engineers who want to learn how to build and use Moving Average forecasting models in Google Sheets. This can be a helpful skill for Software Engineers who want to improve their forecasting accuracy and make better software development decisions.

Reading list

We've selected 12 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 Predict Performance Using MA Forecasting in Google Sheets.
Comprehensive guide to forecasting with exponential smoothing. If you are interested in learning more about forecasting with exponential smoothing, this valuable companion book.
Comprehensive guide to forecasting. If you are interested in learning more about forecasting, this valuable companion book.
Comprehensive guide to deep learning. If you are interested in learning more about deep learning, this valuable companion book.
Comprehensive guide to time series analysis and forecasting. If you are interested in learning more about time series analysis and forecasting, this valuable companion book.
Comprehensive guide to statistical methods for forecasting. If you are interested in learning more about statistical methods for forecasting, this valuable companion book.
Comprehensive guide to time series analysis and its applications with R examples. If you are interested in learning more about time series analysis and its applications with R examples, this valuable companion book.
Similar to the previous textbook, this book comprehensive reference for time series analysis. It is also an appropriate companion book for intermediate to advanced learners.
Practical guide to using Python for data analysis. If you are interested in learning more about data analysis with Python, this valuable companion book.
Comprehensive guide to using Pandas. If you are interested in learning more about data manipulation with Pandas, this valuable companion book.
Great introduction to Python for beginners. If you are new to programming, this book will help you get started quickly.

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