Question 1

What is linear regression?

Accepted Answer

Linear regression fits a straight line (y = mx + b) through a set of data points so that the line best represents the relationship between the independent variable x and the dependent variable y.

Question 2

What is the least squares method?

Accepted Answer

Least squares finds the line that minimizes the sum of the squared vertical distances (residuals) between each data point and the line. This gives the best possible straight-line fit for the data.

Question 3

What do r and R² mean?

Accepted Answer

r is the Pearson correlation coefficient (-1 to 1) measuring the strength and direction of the linear relationship. R² (r squared) is the coefficient of determination (0 to 1) showing the fraction of variance in y explained by the line.

Question 4

How many data points do I need?

Accepted Answer

You need at least 2 distinct x values to fit a line. For a meaningful correlation and reliable predictions, statisticians recommend at least 10 points, but the calculator works with any count of 2 or more.