The following is my response to the question of dummy variable and three ways they may be coded. Please, read if for accuracy.

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"The use of a "dummy" variable is required when a researcher has categorial variables data and wishes to employ the statistical analysis of multiple liner regression. Thus, transforming the nominal variables into a series of "dichotomous" ones which is required for multiple liner regression (Warner, 2013). There are three ways a researcher may then "code" these dummy variables: dummy coding, effect coding, and orthogonal coding. In dummy coding the researcher will assign a value of 0=yes or 1=no "only" to each categorical variable, but there is still no "weighted" differences in the categories, and each group is compared to the reference group. Contrariwise, in effect coding the researcher may assign distinct "weights" to the levels of the categorical data and values other than zero and one are permitted with the caveat that their sum equals to zero i.e., 0 1 -1 0 and like in dummy coding, each group is compared to the reference one. Finally, in orthogonal coding or "uncorrelated independent variables" the researcher is analyzing for "trends" that is a linear relationship between the categorical variables; this is typically employed for "ordinal" categorical data. Note that in each type of coding there will always be one less than then actual or original variables as assigning a code to the last one would be unneeded."