This distinction is particularly relevant when you are investigating cause-effect relationships. It took me the longest time to learn this distinction. But this is entirely backwards!
This distinction is particularly relevant when Variable social meanings are investigating cause-effect relationships.
It took me the longest time to learn this distinction. Of course, I'm someone who gets confused about the signs for 'arrivals' and 'departures' at airports -- do I go to arrivals because I'm arriving at the airport or does the person I'm picking up go to arrivals because they're arriving on the plane!
I originally thought that an independent variable was one that would be free to vary or respond to some program or treatment, and that a dependent variable must be one that depends on my efforts that is, it's the treatment. But this is entirely backwards!
In fact the independent variable is what you or nature manipulates -- a treatment or program or cause. The dependent variable is what is affected by the independent variable -- your effects or outcomes.
For example, if you are studying the effects of a new educational program on student achievement, the program is the independent variable and your measures of achievement are the dependent ones. Finally, there are two traits of variables that should always be achieved.
Each variable should be exhaustive, it should include all possible answerable responses. For instance, if the variable is "religion" and the only options are "Protestant", "Jewish", and "Muslim", there are quite a few religions I can think of that haven't been included.
The list does not exhaust all possibilities. On the other hand, if you exhaust all the possibilities with some variables -- religion being one of them -- you would simply have too many responses. The way to deal with this is to explicitly list the most common attributes and then use a general category like "Other" to account for all remaining ones.
In addition to being exhaustive, the attributes of a variable should be mutually exclusive, no respondent should be able to have two attributes simultaneously. While this might seem obvious, it is often rather tricky in practice.
For instance, you might be tempted to represent the variable "Employment Status" with the two attributes "employed" and "unemployed. But don't we often use questions on surveys that ask the respondent to "check all that apply" and then list a series of categories?
Yes, we do, but technically speaking, each of the categories in a question like that is its own variable and is treated dichotomously as either "checked" or "unchecked", attributes that are mutually exclusive.Social variables are those aspects of a person which may well impact on the way in which they answer a question, speak a language's dialect, what accent they have, where they shop, their politics, etc.
Depending on the context, independent variables are also known as predictor variables, regressors, controlled variables, manipulated variables, or explanatory variables. More generally, the independent variable is the thing that someone actively controls/changes; while the dependent variable is the thing that changes as a result.
A variable is any entity that can take on different values. OK, so what does that mean? OK, so what does that mean?
Anything that can vary can be considered a variable. A variable is any entity that can take on different values. OK, so what does that mean? OK, so what does that mean? Anything that can vary can be considered a variable. If, however, a variable cannot be controlled for, it becomes what is known as a confounding variable.
This type of variable can have an impact on the dependent variable, which can make it difficult to determine if the results are due to the influence of the independent variable, the confounding variable or .
A variable is a factor that can change in quality, quantity, or size, which you have to take into account in a situation. Decisions could be made on the basis of price, delivery dates, or any other variable.