attribute in statistics

What is a variable in statistics?
In statistics, a variable has two defining characteristics: A variable is an attribute that describes a person, place, thing, or idea. The value of the variable can "vary" from one entity to another. For example, a person's hair color is a potential variable, which could have the value of "blond" for one person and "brunette" for another.
What is the opposite of an attribute variable?
The opposite of an attribute variable is an active variable, which is manipulated in an experiment. Although the definition of an attribute variable includes that the variable is “manipulated”, these variables are not the same thing as independent variables. In fact, the nuances of the definition are very subtle, which can lead to confusion.
What is an attribute in data analysis?
In data analysis or data mining, an attribute is a characteristic or feature that is measured for each observation (record) and can vary from one observation to another. It might measured in continuous values (e.g. time spent on a web site), or in categorical values (e.g. red, yellow, green).
What is an attribute variable?
The term “attribute variable” can refer to either an input variable used in statistical software or a manipulated variable used in design of experiments. 1. Usage in Software Some statistical software packages (like Statistica and Minitab) use “attribute variable” as an alternate name for categorical variables. 2. Usage in Experimental Design

Types of Data: Quantitative vs Categorical Variables

Data is a specific measurement of a variable – it is the value you record in your data sheet. Data is generally divided into two categories: 1. Quantitative datarepresents amounts 2. Categorical datarepresents groupings A variable that contains quantitative data is a quantitative variable; a variable that contains categorical data is a categorical

Parts of The Experiment: Independent vs Dependent Variables

Experiments are usually designed to find out what effectone variable has on another – in our example, the effect of salt addition on plant growth. You manipulate theindependent variable (the one you think might be the cause) and then measure thedependent variable (the one you think might be the effect) to find out what this effect might be. You wil

Other Common Types of Variables

Once you have defined your independent and dependent variables and determined whether they are categorical or quantitative, you will be able to choose the correct statistical test. But there are many other ways of describing variables that help with interpreting your results. Some useful types of variables are listed below. scribbr.com

Other Interesting Articles

If you want to know more about statistics, methodology, or research bias, make sure to check out some of our other articles with explanations and examples. scribbr.com

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