The time series component that reflects the irregular changes in a time series that are not caused by any other component, and tends to hide the existence of the other more predictable components, is called:
a. trend.
b. cyclical.
c. seasonal.
d. random variation.
The Correct Answer and Explanation is :
The correct answer is d. random variation.
Explanation:
In time series analysis, a time series is typically broken down into several components that help explain its structure. These components include the trend, cyclical, seasonal, and random variations.
- Trend: This represents the long-term movement in the data over time. It shows the general direction in which the data is moving, either upward, downward, or remaining stable. Trends can be caused by factors such as population growth, technological changes, or economic conditions.
- Cyclical: Cyclical variations are fluctuations in a time series that occur at irregular intervals, typically due to business cycles or economic factors. These patterns are often difficult to predict and do not occur at fixed periods like seasonal variations.
- Seasonal: Seasonal variations are predictable and recurring fluctuations in a time series that occur at regular intervals, such as yearly, monthly, or weekly. For example, retail sales often increase during the holiday season or summer months.
- Random Variation: Random variation, also known as “noise,” refers to the irregular, unpredictable fluctuations that are not explained by the trend, seasonal, or cyclical components. These variations are due to random or irregular events that cannot be attributed to any specific pattern or cause. Random variation tends to obscure the more predictable components, making it difficult to identify underlying trends or patterns in the data. For instance, in stock prices, random events such as unexpected market news or natural disasters can cause sudden, unpredictable changes.
Random variation is essentially the “background noise” in time series data that can make it harder to identify the other components such as trends and seasonal effects. It represents the unpredictable and irregular fluctuations that are unrelated to any other discernible patterns.
Let me generate an image that illustrates these components in a time series.
Here is the illustration of a time series graph that shows the different components: trend, cyclical, seasonal, and random variation. You can clearly see how random fluctuations can obscure the other more predictable components. Let me know if you need further clarification or modifications!