Linear Regression

3. A point whose x-value is the mean of all the x-values of the points on the scatter plot and its y-value is the mean of all the y-values of the points on the scatter plot.
7. An unknown or unobserved factor that influences the dependent variable.
8. This method creates a regression line for a scatter plot where the line must contain the centroid and the sum of the squares formed is at a minimum.
11. Using a linear regression to make predictions within the data set.

1. It indicates how close the data are to the line of best fit. Is represented as a number between -1 and 1.
2. Measures how well the graph of a regression fits the data. It represents the percentage of variation of the observed values of the data points from their predicted values.
3. A factor that influences both the independent and dependent variables.
4. To make predictions for values of x that are outside of the data set.
5. When one event affects the outcome of a second event.
6. The vertical distance between an observed data value and its predicted value using a regression equation.
9. Drawn through a scatter plot of data points to show the best linear relationship between an independent variable and a dependent variable.
10. The rate of change for a situation describes the amount that the dependent variable changes compared to the amount the independent variable changes.