Under вЂњNew Value,вЂќ type a вЂњ1,вЂќ then click вЂњAdd.вЂќ On the вЂњOld ValueвЂќ side, select the вЂњAll Other ValuesвЂќ button and type вЂњ0вЂќ as the new value. Under вЂњOld Value,вЂќ enter the category value to be recoded.

Recode the values of the variable by coding one category as a вЂњ1вЂќ and the others as zero.

Click вЂњ Change.вЂќ Click вЂњ Old and New Values,вЂќ which opens a new display, showing old and new values for the variable you want to transform.

Click the вЂњ Output VariableвЂќ name box and type a name for your new dichotomous variable.

Select the variable you want to recode, and then click the arrow, which moves the variable name into the box labeled вЂњ Numeric Variable.вЂќ This opens a window that displays the variables in your data set.

Click the вЂњ TransformвЂќ menu at the top of the SPSS data sheet, then select вЂњ Recode Into Different Variable,вЂќ because you will transform the categorical variable into one or more dichotomous or dummy variables.

A person with a zero in these categories would be counted as independent). A person who identifies as one of these would be coded a вЂњ1вЂќ in the data set. For example, a categorical variable on political affiliation with three categories - Democrat, Republican and Independent - would be dummy coded into two dichotomous variables, such as Democrat and Republican. (Note the number of categories, remembering that dummy coding transforms a variable with вЂњnвЂќ categories into вЂњn-1вЂќ categories. Select the categorical variable that you want to dummy code.LetвЂ™s walk through the steps! Dummy Coding Step by Step This process is known as вЂњdummy coding.вЂќ IBM SPSS makes dummy coding an unpretentious practice. An example would be employed and unemployed. These steps involve coding a categorical variable into multiple dichotomous variables, in which variables take the value of вЂњ1вЂќ or zero.ДЇor clarity, a dichotomous variable is defined as a variable that splits or groups data into 2 distinct categories. Including these variables in an analytical model requires special steps to ensure the results can be interpreted properly. Statistical Analysis often include s variables in which the numbers represent qualitative categories (such as gender, ethnicity or political affiliation). If we consider a morning latte example, we might note the following: With some guidance, you can craft a data platform that is right for your organizationвЂ™s needs and gets the most return from your data capital.

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