Concepts of Misleading Graphs and Statistics

Data can be displayed in many different ways. Sometimes, people who make graphs choose to display data in a misleading way

A pictograph can be misleading by using different sizes of the objects

The use of a different scale on a graph can influence conclusions drawn from the graph

To interpret a line graph and a bar graph correctly, note the scale

Other ways that the graphs are misleading are if there is no title, there are no labels on the axis or scales, the axis is broken or the intervals on the scales are not equal

Statistics is often used to make advertisements visually appealing

When dealing with statistics, the information must be interpreted carefully

The different measures of central tendency (mean, median, and mode) can be used to show different points of view

When information is gathered about a group, the entire group is called a population. Researchers often use study a part of the population, called a sample

For a random sample, the members of the population are chosen at random. This gives every member of the population an equal chance of being chosen

A convenience sample is based on the members of the population that are readily available. Both convenience and biased samples do not represent the data fairly

A random sample is more likely to be a representative of a population than a convenience sample

Given data about a random sample, you can use proportional reasoning to make predictions or verify claims about the entire population