How to interpret a time-series plot?

A time-series plot shows how a variable changes over time. It can be used to identify trends, patterns and anomalies.

To interpret a time-series plot, start by looking at the overall trend. Is it increasing, decreasing or staying the same? If there is a clear trend, you can use regression analysis to estimate the rate of change. If there are fluctuations around the trend, you can look for seasonal patterns or cycles. This can be done by calculating the moving average or using a seasonal decomposition method.

Next, look for any outliers or anomalies. These are data points that are significantly different from the rest of the data. They can be caused by errors in measurement or unusual events. It is important to investigate these outliers to determine if they are genuine or not.

Finally, consider the overall shape of the plot. Is it linear, exponential or logarithmic? This can give you an idea of the underlying process that is driving the data. For example, a linear trend may indicate a steady increase or decrease, while an exponential trend may indicate growth or decay that is accelerating over time.

Overall, interpreting a time-series plot requires careful observation and analysis. By identifying trends, patterns and anomalies, you can gain insights into the underlying process that is driving the data.