Time Series-Quiz

What is a common forecasting method used in hierarchical time series analysis?

• Top-up approach

• Bottom-up approach

• Moving Average Method

• Time-Series Decomposition

How does the bottom-up approach differ from the top-down approach in aggregation strategies?

• The bottom-up approach aggregates from detailed data to a summary, while the top-down approach starts with a summary and breaks it down into details.

• Both approaches aggregate data in the same way, focusing on the same level of detail.

• The bottom-up approach is faster than the top-down approach because it requires less data processing.

• The bottom-up approach starts with a summary and breaks it down into details, while the top-down approach aggregates from detailed data to a summary.

Explain the concept of aggregation in the context of hierarchical time series.

• Aggregation in hierarchical time series is the process of summarizing data from lower levels of a hierarchy to higher levels, enabling analysis of overall trends.

• Aggregation involves analyzing individual data points without summarizing them.

• Aggregation is only applicable to flat time series data.

• Aggregation refers to the process of collecting data without any hierarchy.

How can you identify seasonal patterns in a time series dataset?

• Use visual inspection, decomposition methods, ACF analysis, and seasonal subseries plots.

• Use linear regression analysis only

• Ignore outliers in the dataset

• Focus solely on the mean values of the data

Describe a situation where a middle-out approach might be beneficial in hierarchical forecasting.

• A middle-out approach is ineffective in any forecasting scenario.

• A middle-out approach is beneficial in a retail company forecasting sales at regional levels to improve accuracy by integrating store and national data.

• A middle-out approach focuses solely on individual store performance without considering regional data.

• A middle-out approach is used only for financial forecasting at the corporate level.

What are some challenges associated with forecasting in hierarchical time series?

• Forecasting is always accurate in hierarchical time series.

• There are no challenges in hierarchical time series forecasting.

• Data quality is never an issue in forecasting.

• Challenges include consistency across levels, model complexity, data quality issues, and aggregation method impacts.

Determine the appropriate components of time series for the situation below:

The sales of school uniforms during the year-end school holiday.

• Trend

• Seasonal Variations

• Cyclical Variations

• Irregular fluctuations

In what scenario would you prefer a top-down approach in hierarchical forecasting?

• When detailed data is available for all levels.

• When you want to forecast at a high level and distribute the forecast downwards.

• When individual forecasts are more reliable than aggregated ones.

• When there is no need for aggregation.

The __________ component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer

• Trend 
• Seasonal
• Cyclical
• Randomness

Which one of the following statement BEST describes the time series plot for the period shown?

• It shows no trend and no change in variability

• It shows increasing linear trend with constant variability

• It shows increasing trend with decreasing variability

• It shows increasing linear trend with increasing variability