residuals, residual plot - The difference between the observed value (the data) and the predicted value (the y-value on the regression line). Positive values for the residual (on the y-axis) mean the prediction was too low, and negative values mean the prediction was too high; means the guess was exactly correct, Line of Best Fit or Linear Regression - The line (written in y=mx+b form) that best models the data by minimizing the distance between the actual points and the predicted values on the line., bivariate data - Deals with two variables that can change and are compared to find relationships. If one variable is influencing another variable, then you will have bivariate data that has an independent and a dependent variable (ordered pairs). This is because one variable depends on the other for change., Causation - Tells you that a change in the value of the x-variable will cause a change in the value of the variable., Correlation - The extent to which two numerical variables have a linear relationship. A correlation gives you a number , (the correlation coefficient) which can range from to . Zero correlation means there is no relation between two variables. A correlation of (either + or -) means perfect correlation., observed value - The value that is actually observed (what actually happened)., scatter plot - A display of bivariate data (ordered pairs) organized into a graph. A scatter plot has two dimensions, a horizontal dimension (x-axis) and a vertical dimension (the y-axis). Both axes contain a number line.,

Modeling Data Vocab

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