Final answer:
To measure seasonal effects, a time series plot is constructed, which shows how a variable changes over time by representing it on a graph with time on the horizontal axis and the variable on the vertical axis.
Step-by-step explanation:
In order to measure seasonal effects, we must construct a time series plot. A time series plot is a graphical representation that tracks changes over time for a given data set. Data is plotted on a graph where the horizontal axis represents the sequential order of time and the vertical axis represents the variable being measured, such as temperature or unemployment rates. It is a useful tool for observing trends and patterns that may occur in the data due to seasonal variations or other time-based factors.
For example, when we consider data like monthly temperatures or yearly unemployment rates, a time series plot helps us visualize how these values change over the months or years. By connecting the data points in chronological order, we can easily see upward or downward trends and seasonal fluctuations.