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Variables

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VARIABLE

Trochim (2006) defined a variable as an object, event, idea, feeling, time period, or any other type of category you are trying to measure. On the other hand, Moore and George (1993) defined a variable as any characteristic of a person or thing that can be expressed as a number whilst Frank, Little and miller (200) defined a variable as any factor that can change in an experiment. Anything that can vary can be considered a variable. For instance, age can be considered a variable because age can take different values for different people or for the same person at different times. A value of the variable is the actual number that describes a particular person or thing (Moore and George, 1993). For example, Height and sex are variables that describe people. Moore and George (1993) continue to say that there are two types of variables and these are quantitative variables and categorical variables. A quantitative variable takes numerical values for which arithmetic operations such as differences and averages make sense. A categorical variable simply records into which of several categories a person or thing falls. Variables measured as numbers in a scale of equal units, such as height in centimeters are quantitative variables. Examples of categorical variables include sex and age.

INDEPENDENT VARIABLE

An independent variable is exactly what it sounds like. Moore and George (1993) defined independent variables as explanatory variables. On the other hand, Shuttleworth (2008) defined an independent variable as a factor manipulated by the researcher, and it produces one or more results known as dependent variables. The term independent variable is often a source of confusion as many people assume that the name means that the variable is independent of any manipulation. The name arises because the variable is isolated from any other factor, allowing experimental manipulation to establish analyzable results. It is a variable that stands alone and isn't changed by the other variables you are trying to measure. Independent variable is controlled by the researcher and evaluated by its measurable effect on the dependent variable or variables. For example, someone's age might be an independent variable. Other factors such as what they eat, what they wear can not change a person's age. In fact, when someone is looking for some kind of relationship between variables she or he is trying to see if the independent variable causes some kind of change in the other variables, or dependent variables (Shuttleworth, 2008).

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