The overall direction of deaths is downward from May to early July, then upward from July to September, and finally downward again towards October.

Shows the general direction in which data is moving over time, ignoring short-term fluctuations.

-The long-term movement or direction in the data.

-Indicates whether values are increasing, decreasing, or stable over time.

-For example: A retail store’s total sales steadily increase every year as the business expands.

The long-term progression or direction of the data over time.

Example, graph of ice cream sales peaking in summer and dropping in winter.

This graph shows a long-term upward trend. Trend represents the overall direction in which data moves over time, either increasing, decreasing, or stable.

Example:

An example is the increasing number of internet users over the past decade.

This graph displays repeating patterns that occur at regular intervals. Seasonality is often driven by time of year, weather, holidays, etc.

Example:

Ice cream sales peak in summer and drop in winter every year — this is a seasonal pattern.

Example:

Global Average Temperature

Example:

Retail sales spike during holidays (e.g., Black Friday or Christmas).

Graph Example: A steadily increasing sales figure over several years.

Explanation: Trends reflect persistent, long-term growth or decline, unaffected by short-term fluctuations. For instance, global temperature rise over decades.

-Regular, repeating patterns that occur at fixed intervals (daily, monthly, and yearly).
-Sales spike every January due to holiday shopping such as Chinese New Year.

The graph illustrates waves over a longer period without fixed intervals. Cyclical components reflect economic or business cycles.

Example:

The housing market rising and falling every few years due to economic conditions is cyclical behavior.

This graph shows random, unpredictable fluctuations. Irregular components are caused by unexpected events such as natural disasters or global crises.

Example:

A sudden drop in air travel during COVID-19 is an irregular pattern.

Example, the GDP growth on the Malaysia plantation sector.

Example:

Stock market cycles or real estate price cycles over many years.

-Fluctuations over longer, variable periods, usually linked to economic cycles

-It can go up and down like seasonal patterns, but follows the overall trend and depends on the broader economic environment.

-Example: During a recession, sales may decline for a few years, during an economic boom, sales may gradually rise.

- Unpredictable variations remaining after trend, seasonal, and cyclical effects are removed.

-Example: A sudden drop in sales due to a natural disaster, such as flooding that forces store closures.

Key Traits: Fluctuations that rise and fall but are not seasonal. Unlike seasonal variations, cyclical cycles are not fixed in length or timing.

Example: Long-term changes in GDP due to economic cycles.

Key Characteristics:

Unpredictable Variations: These are erratic changes that do not follow a pattern and are often due to unforeseen events.

Short-Term Effects: Typically, these fluctuations are short-lived and do not persist over time.

Examples: Sudden market crashes, natural disasters, or unexpected political events impacting economic indicators.

Graph Description: The graph above illustrates a time series with irregular fluctuations, showing random spikes and drops without any discernible pattern, emphasizing the unpredictable nature of this component.