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# What is a dichotomous variable?

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Dichotomous variables are variables that have two levels. A very common example of a dichotomous variable is gender, which has two outcomes and is reported as male or female.

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Dichotomous variables are part of a larger type of variable called a categorical variable. Categorical variables are not measured by numbers, but they can instead be categorized. Dichotomous variables are any categorical variable that has two distinct outcomes. Survey questions that yield yes or no answers are also examples of dichotomous variables. When formulating hypotheses to test a dichotomous variable, it is essential to test the variables as mutually exclusive. This means that one outcome excludes the possibility of the other outcome.

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## Related Questions

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Two examples of lurking variables are the color of a paper airplane and its ability to fly and the size of the thymus in children who developed SIDS in the early 1900s. Neither of the two factors are responsible for either effect. A lurking variable is an extraneous variable that does not play a role in determining the relationship between the independent and the dependent variable.

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Statistical significance shows the mathematical probability that a relationship between two or more variables exists, while practical significance refers to relationships between variables with real-world applications, according to California State University, Long Beach. Two or more variables do not need statistical significance to have practical significance, and vice versa.

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Unequal class intervals can be used in frequency distribution if the rate of occurrence is very unevenly distributed, with certain classes showing far lower or far greater frequencies than those on either side. In many data tables and histograms, consistent intervals are used, but they cannot always account for irregularities and outliers like those that strategically use unequal intervals.