A bar graph is a pictorial rendition of statistical data in which the independent variable can attain only certain discrete values. The dependent variable may be discrete or continuous. In a horizontal bar graph, the independent variable is plotted along a vertical axis from the bottom up.

A typical bar graph has a label or title, x-axis, y-axis, scales or increments for the axis, and bars. Some graphs may also have a legend that specifies what various colors represent, such as in a stacked bar graph. Bar graphs are ideal for comparing two or more values, or values over time.

Graphs have two axes, the lines that run across the bottom and up the side. The line along the bottom is called the horizontal or x-axis, and the line up the side is called the vertical or y-axis.

A bar graph breaks categorical data down by group, and represents these amounts by using bars of different lengths. It uses either the number of individuals in each group (also called the frequency) or the percentage in each group (called the relative frequency).

This is similar to a 3-D column but should only be used for continuous data. Bar graphs with multiple, independent variables. Bar graphs are used for making comparisons between discrete cases or to look for trends (usually over space or time).

The independent variable here is the YEAR and it is plotted on the horizontal axis. The dependent variable is the AVERAGE HEIGHT and this is plotted on the vertical axis.

Bar graphs have a labeled x-axis (horizontal axis) and y-axis (vertical axis). When experimental data is graphed, the independent variable is graphed on the x-axis, while the dependent variable is graphed on the y-axis.

The independent variable belongs on the x-axis (horizontal line) of the graph and the dependent variable belongs on the y-axis (vertical line).

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause, while a dependent variable is the effect. In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable.

The dependent variable is the variable that is being measured or tested in an experiment. 1 For example, in a study looking at how tutoring impacts test scores, the dependent variable would be the participants’ test scores, since that is what is being measured.

An independent variable is a variable that represents a quantity that is being manipulated in an experiment. A dependent variable represents a quantity whose value depends on those manipulations.

What is another word for outcome variable?

In statistical modeling, the predictor variable is analogous to an independent variable and is used to predict an outcome (the criterion variable). One of the main differences between independent/dependent and criterion/predictor variables is the concept of causation.