AS91580 Investigate Time-Series Data Internal, 4 credits Investigate Time-Series Data Internal, 4 credits

Introduction... Time-Series data is data collected from a single variable at regular periods over an extended period of time. The single variable describes one aspect of a continuous activity.

Typical activities include: retail business share market sports records weather records scientific observations biometrics - weight, height etc changes in a population

The single variable is an example of continuous data. The data records how the variable changes over time. Examples include product sales, rainfall, infant weight, plant height. Single Variable

All graphs are TIme-Series. This means that: Graphs time variable The x-axis is always time The y-axis is the variable The data can be plotted as a line-graph OR a scatter-plot with a line-of-best-fit Never rule lines between data points - use a smooth curve

Patterns and Trends Over time, the value of the variable can change. Such variations can be: Short-term Long-term - general pattern over an extended period of time, ignores short-term variations. Seasonal, or cyclic patterns - a rise-fall pattern that repeats on a regular basis

Seasonal Variations natural patterns include the occurance and intensity of sunspots. The radiation given off by sunspots affect communication satellites,so by predicting sunspots satellites can be turned off to protect them from damage. The extent of sea ice at the poles is affected by the season. If you look carefuly, you can se a steady decrease in the annual peak coverage in the Arctic. Seasonal patterns are frequently controlled by natural patterns. For example, bikini sales peak in summer and drop off in winter, while the reverse is true for sales of electric blankets.

long-term trends long-term trends are often only apparent when enough data has been gathered to identify short-term and seasonal variations. The retreat of the polar ice caps is a current example. The last graph was of a short time period, and the long-term trend was barely noticeable. But by graphing only the peak coverage for a period of many years, the true trend becomes apparent.

Changes in a Pattern A pattern can be altered by external events for example new laws, wars or catastrophes. The price of oil is volatile, as this graph shows. This next graph is familiar - it shows the levels of CO 2 in the atmosphere. The start of the current rise ( ∼ 1750) is when the Industrial revolution began. What happened in the 1960’s to cause birth rates to fall so much? Such changs in external conditions are often permanent. The changes to the trend can be positive, negative, or to nullify prior trends, creating a plateau.

outliers... outliers are random events that cause the variable to have a single data value that is significantly different from the rest. Outliers can have both strong and weak effects upon the overall trend, sometimes giving a distorted interpretation. For this reason two analyses are typically performed - one with all data, the other excluding the outliers. There are detailed stat calculation methods to identify outliers from very large data sets.

and lastly...consider this graph!