You manipulate the independent variable(the one you think might be the cause) and then measure the dependent variable (the one you think might be the effect) to find out what this effect might be. Parts of the experiment: Independent vs dependent variablesД®xperiments are usually designed to find out what effect one variable has on another вЂ“ in our example, the effect of salt addition on plant growth. This example sheet is color-coded according to the type of variable: nominal, continuous, ordinal, and binary. To gather information about plant responses over time, you can fill out the same data sheet every few days until the end of the experiment. To keep track of your salt-tolerance experiment, you make a data sheet where you record information about the variables in the experiment, like salt addition and plant health. For example, star ratings on product reviews are ordinal (1 to 5 stars), but the average star rating is quantitative. *Note that sometimes a variable can work as more than one type! An ordinal variable can also be used as a quantitative variable if the scale is numeric and doesnвЂ™t need to be kept as discrete integers.

Groups that are ranked in a specific order. Groups with no rank or order between them. Binary vs nominal vs ordinal variables Type of variableД«inary variables (aka dichotomous variables) There are three types of categorical variables: binary, nominal, and ordinal variables. They are sometimes recorded as numbers, but the numbers represent categories rather than actual amounts of things. Measurements of continuous or non-finite values.Д¬ategorical variables represent groupings of some kind. Number of different tree species in a forestД¬ontinuous variables (aka ratio variables).Discrete vs continuous variables Type of variableДiscrete variables (aka integer variables) There are two types of quantitative variables: discrete and continuous. When you collect quantitative data, the numbers you record represent real amounts that can be added, subtracted, divided, etc. Each of these types of variable can be broken down into further types. Data is generally divided into two categories:ДЄ variable that contains quantitative data is a quantitative variable a variable that contains categorical data is a categorical variable.

Types of data: Quantitative vs categorical variablesДata is a specific measurement of a variable вЂ“ it is the value you record in your data sheet. Frequently asked questions about variables.Parts of the experiment: Independent vs dependent variables.Types of data: Quantitative vs categorical variables.

Numeric variable