Data Science Time Series Analysis 2

Question 1

In ARIMA(p, d, q), what does the parameter 'd' represent?

Accepted Answer

The number of times the data is differenced to achieve stationarity

Answer

The 'd' parameter in ARIMA is the integration order — it specifies how many times the series must be differenced to remove non-stationarity such as trends.

Question 2

The Augmented Dickey-Fuller (ADF) test is primarily used to:

Accepted Answer

Test whether a time series has a unit root and is non-stationary

Answer

The ADF test checks for a unit root in the series — rejecting the null hypothesis (unit root present) provides evidence that the series is stationary.

Question 3

In simple exponential smoothing, the smoothing parameter α controls:

Accepted Answer

The rate at which the influence of older observations decays

Answer

α (between 0 and 1) determines how quickly past observations lose influence — a higher α means more weight on recent data and faster adaptation to changes.

Question 4

What is the primary purpose of time series decomposition?

Accepted Answer

To separate the series into trend, seasonality, and residual components

Answer

Time series decomposition breaks a series into its underlying components — trend, seasonal pattern, and irregular residuals — to better understand and model each element separately.

Question 5

A simple moving average of order k is computed as:

Accepted Answer

The arithmetic mean of the k most recent observations

Answer

A simple moving average of order k computes the unweighted arithmetic mean of the k most recent data points, smoothing short-term fluctuations to reveal underlying trends.

Data Science Practice Test

Data Science Practice Test

Data Science Time Series Analysis 2