DSE Time Series Analysis and Forecasting 3

Question 1

What capability does a SARIMA model add over a standard ARIMA model?

Accepted Answer

Explicitly capturing repeating seasonal patterns

Answer

SARIMA (Seasonal ARIMA) extends ARIMA by incorporating additional seasonal AR, differencing, and MA terms to model patterns that repeat at fixed seasonal intervals.

Question 2

Why is walk-forward (time series cross-validation) preferred over standard k-fold cross-validation for time series data?

Accepted Answer

It respects temporal ordering and prevents future data from leaking into the training set

Answer

Walk-forward validation trains on past data and evaluates on sequentially later windows, preserving time order and preventing data leakage that would inflate accuracy estimates.

Question 3

Facebook Prophet is best described as which type of forecasting tool?

Accepted Answer

A decomposable additive model that handles trends, seasonality, and holiday effects automatically

Answer

Prophet is an additive model that decomposes time series into trend, multiple seasonality components, and user-specified holiday effects, designed to work well on business forecasting problems.

Question 4

In time series analysis, what does 'cointegration' describe?

Accepted Answer

A long-run equilibrium relationship between two or more individually non-stationary series

Answer

Cointegration exists when two or more non-stationary series share a long-run equilibrium such that a linear combination of them is stationary, despite each wandering individually.

Question 5

Why are Long Short-Term Memory (LSTM) networks preferred over standard RNNs for long time series sequences?

Accepted Answer

LSTMs use gating mechanisms to solve the vanishing gradient problem, enabling learning of long-range dependencies

Answer

LSTMs employ input, forget, and output gates that control information flow through the network, solving the vanishing gradient problem that prevents standard RNNs from learning distant dependencies.

DSE - Data Science Practice Test

DSE - Data Science Practice Test

DSE Time Series Analysis and Forecasting 3