Forecasting Basics

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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?

The longer the horizon, the lower the accuracy Signup and view all the answers

What is an example of a time series model?

International airline passenger forecast Signup and view all the answers

What is involved in time series modeling?

Plotting demand data on a time scale Signup and view all the answers

What is a time series?

A sequence of observations taken at regular intervals Signup and view all the answers

What is the primary purpose of analyzing a time series?

To identify any trends, seasonal factors, cyclical factors, or random factors Signup and view all the answers

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

To compare the forecasts with historical data and estimate the error Signup and view all the answers

What is a sequence plot used for in forecasting?

To get a visual impression of the presence of certain behavioral components Signup and view all the answers

What is the purpose of specifying a forecasting model?

To select the variables to be included and estimate the parameters Signup and view all the answers

What is the third step in the forecasting process?

Verifying and validating the model Signup and view all the answers

What is a characteristic of a stationary model?

It assumes a constant mean and random variation only Signup and view all the answers

What is the main advantage of the Naïve Forecast model?

It is simple and flexible Signup and view all the answers

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

The forecast becomes more stable Signup and view all the answers

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

Stability vs. responsiveness Signup and view all the answers

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

It is highly responsive to change and trends Signup and view all the answers

What is the purpose of measuring forecast error?

To evaluate the performance of a forecasting model Signup and view all the answers

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

Concluding which forecasting method is most accurate Signup and view all the answers

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

Random variation Signup and view all the answers

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

Fitting a trend equation to historical data Signup and view all the answers

What is the limitation of using trend analysis for forecasting?

It should not be used to forecast more than half the number of time periods used to generate the forecast Signup and view all the answers

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

To adjust for variations at certain periods Signup and view all the answers

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

Ŷ = T * S – C Signup and view all the answers

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

Comparing the performance of classical and modern methods on a large set of univariate time series forecasting problems 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?

Classical methods like ETS and ARIMA Signup and view all the answers

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

They make stronger assumptions about the data, allowing them to learn faster 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?

They need to estimate the autocorrelation structure from the data Signup and view all the answers

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

The model will lead to lots of bad predictions 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?

Multi-step forecasting on univariate datasets Signup and view all the answers