Forecasting Basics

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Questions and Answers

What is the main purpose of forecasting?

  • To measure the accuracy of previous forecasts
  • To execute a business plan
  • To analyze trends and seasonal factors
  • To get the complete picture of future performance (correct)

What is a characteristic of a good forecast?

  • It is only used for short-term planning
  • It is based on a single variable
  • It contains an error measure (correct)
  • It is always 100% accurate

What is a key difference between time series models and regression models?

  • Regression models are only used for short-term forecasting
  • Time series models use only time as an independent variable (correct)
  • Time series models are more accurate than regression models
  • Regression models are more complex than time series models

What is a common challenge of forecasting?

<p>The longer the horizon, the lower the accuracy (C)</p> Signup and view all the answers

What is an example of a time series model?

<p>International airline passenger forecast (D)</p> Signup and view all the answers

What is involved in time series modeling?

<p>Plotting demand data on a time scale (D)</p> Signup and view all the answers

What is a time series?

<p>A sequence of observations taken at regular intervals (C)</p> Signup and view all the answers

What is the primary purpose of analyzing a time series?

<p>To identify any trends, seasonal factors, cyclical factors, or random factors (A)</p> Signup and view all the answers

What is the purpose of verifying and validating a forecasting model?

<p>To compare the forecasts with historical data and estimate the error (D)</p> Signup and view all the answers

What is a sequence plot used for in forecasting?

<p>To get a visual impression of the presence of certain behavioral components (A)</p> Signup and view all the answers

What is the purpose of specifying a forecasting model?

<p>To select the variables to be included and estimate the parameters (B)</p> Signup and view all the answers

What is the third step in the forecasting process?

<p>Verifying and validating the model (A)</p> Signup and view all the answers

What is a characteristic of a stationary model?

<p>It assumes a constant mean and random variation only (D)</p> Signup and view all the answers

What is the main advantage of the Naïve Forecast model?

<p>It is simple and flexible (B)</p> Signup and view all the answers

In a Moving Average model, what happens as the value of 'n' increases?

<p>The forecast becomes more stable (B)</p> Signup and view all the answers

What is a trade-off in selecting the value of 'n' in a Moving Average model?

<p>Stability vs. responsiveness (A)</p> Signup and view all the answers

What is a characteristic of a 2-period moving average model?

<p>It is highly responsive to change and trends (D)</p> Signup and view all the answers

What is the purpose of measuring forecast error?

<p>To evaluate the performance of a forecasting model (D)</p> Signup and view all the answers

What is the primary effect of selecting an error measure in forecasting?

<p>Concluding which forecasting method is most accurate (C)</p> Signup and view all the answers

In the general form of time series models, what does the symbol ε represent?

<p>Random variation (B)</p> Signup and view all the answers

What is the primary purpose of trend analysis in time series forecasting?

<p>Fitting a trend equation to historical data (D)</p> Signup and view all the answers

What is the limitation of using trend analysis for forecasting?

<p>It should not be used to forecast more than half the number of time periods used to generate the forecast (C)</p> Signup and view all the answers

What is the purpose of a seasonal index in time series analysis?

<p>To adjust for variations at certain periods (C)</p> Signup and view all the answers

What is the practical forecast form of a time series model?

<p>Ŷ = T * S – C (B)</p> Signup and view all the answers

What was the primary focus of the recent study mentioned in the text?

<p>Comparing the performance of classical and modern methods on a large set of univariate time series forecasting problems (D)</p> Signup and view all the answers

Which type of models tend to outperform machine learning and deep learning methods for one-step forecasting on univariate datasets?

<p>Classical methods like ETS and ARIMA (A)</p> Signup and view all the answers

What is a key advantage of classical models in terms of learning?

<p>They make stronger assumptions about the data, allowing them to learn faster (A)</p> Signup and view all the answers

Why do machine learning and deep learning models require more data and epochs to train compared to classical models?

<p>They need to estimate the autocorrelation structure from the data (A)</p> Signup and view all the answers

What is a potential consequence of using a high-powered deep learning tool on a small dataset?

<p>The model will lead to lots of bad predictions (D)</p> Signup and view all the answers

What type of forecasting problem do classical models like Theta and ARIMA tend to outperform machine learning and deep learning methods?

<p>Multi-step forecasting on univariate datasets (B)</p> Signup and view all the answers

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