This technique makes no a priori assumption of whether one variable is dependent on the other(s) and is not concerned with the relationship between variables; instead it gives an estimate on the degree of association between the variables: a. Regression
b. Multiple regression
c. Means test
d. Correlation

d. Correlation

Step-by-step explanation:

Based on the information being provided it can be said that this technique provides the correlation between two or more variables. Correlation explains any statistical relationship that exists between two different variables or sets of data, whether it is casual or not. Many times it is the degree to which a pair of variables are linearly related

y = 2x

step-by-step explanation:

if you divide each number in the sequence, you'll see that they all have a multiple factor of 2. each number in the series, and any other numbers which may continue, will be multiplied by 2. therefore, y is the next number in the sequence, and x is the current one, so, our formula will be y = 2x.