The k-Means algorithm uses a similarly metric of distance between a record and a cluster centroid. If the attributes of the records are not quantitative but categorical in nature, such as Income Level with values {low, medium, high} or Married with values {yes, no} or State of Residence with values {Alabama, Alaska,..., Wyoming} then the distance metric is not meaningful. Define a more suitable similarity metric that can be used for clustering data records that contain categorical data.