A trend line analysis is also known as regression analysis. In this type of analysis, a line is plotted between two or more points on a graph. These points represent some sort of data, such as the price of an individual stock at a given point in time. Analysts use the overall direction or slope of the trend line to predict changes or determine averages.
The study of statistics introduces trend line analysis as a method of determining what has occurred or is occurring. For example, real estate professionals can plot home sales prices according to home features and neighborhood location to determine an average market price. Some statistical programs can manipulate stored data according to several variables. Differences in the average price for two bedroom homes that have a fireplace versus those homes that do not can be instantly compared with a computerized trend line analysis.
In a trend line analysis, a graph is used to plot data points for two variables along the x and y axes. When a stock analyst wishes to determine the average trend of a company's stock price, he will plot points on a graph, with each point representing a daily price of the stock. The price will most likely be plotted against the y axis, while the date will be plotted against the x axis. The graph will show a series of fluctuating data points according to increases and decreases in the company's stock price over time.
Trend lines do not necessarily connect between all data points in a graph. One of the most important factors behind a trend line analysis is validity. In order for the analysis to be reliable, a trend line should pass through data points that are not spaced unevenly. This ensures that short-term spikes or downfalls are not used to predict long-term changes.
In most instances, an accurate trend line analysis will plot a line between data points that are evenly spaced from each other. The line usually indicates either an upward or downward slope. At times, the line slopes upwards for a period of time and then begins to reflect a downward trend. For example, a company's net profit over the past 20 years may show an overall increase during years five through ten and then show an overall decrease between years 15 through 20. Analysts typically predict impending changes using breaks in a line's trend.
Predicting changes in aggregates or trends is a common practice in economics. Analysts often use data, such as gross domestic product, hiring trends, consumer price indexes, and commercial ordering activity to predict changes in an economy's overall health. Besides predictions, a trend analysis of this data can document periods of economic expansion or recession.
