A technique which minimizes sum of squared vertical difference, to determine regression line is considered as

The correct answer is C. least square technique.

Least squares is a method of estimating the parameters of a statistical model. It is the most common method of fitting a line to a set of data points. The least squares line is the line that minimizes the sum of the squared distances between the data points and the line.

The least squares technique is used in a variety of fields, including statistics, economics, and engineering. It is a powerful and versatile tool that can be used to fit a line to a wide variety of data sets.

The other options are incorrect because they do not accurately describe the least squares technique.

• Option A, negative square technique, is incorrect because the least squares technique minimizes the sum of squared distances, not the sum of negative squared distances.
• Option B, positive square technique, is incorrect because the least squares technique minimizes the sum of squared distances, not the sum of positive squared distances.
• Option D, most square technique, is incorrect because the least squares technique minimizes the sum of squared distances, not the sum of most squared distances.