Statistics Chapter 9 Vocabulary Crossword

2. A measure of the strength and direction of a linear relationship between two variables across a sample of a population.
7. Y in an ordered pair (X, Y).
9. Calculated by subtracting the mean from each y-value in the data set.
10. It indicates how much the observed y-values deviate from the predicted regression line, with smaller values signifying a more accurate model.
17. Y-hat equals m times x plus b.
18. A relationship between two variables. There are four types: negative, positive, none, and nonlinear.
19. The sum of the squares of the differences between each predicted y-valued the mean of y.
20. t equals r divided by the square root of 1 minus r squared over n minus 2.

1. Calculated by subtracting each predicted y-value from the corresponding y-value in the data set.
3. The square of the sample correlation coefficient. The ratio of the explained variation to the total variation.
4. Calculated by subtracting the mean from each predicted y-value in the data set.
5. A measure of the strength and direction of a linear relationship between two variables across an entire population. Represented by p.
6. The sum of squares of the difference between the y-value of each ordered pair and each corresponding predicted y-value.
8. The level of significance is denoted by (α) the lowercase Greek letter alpha.
11. Also called line of best fit. The line for which the sum of squares of the residuals is a minimum. Can be used to predict the value of y for a given value of x.
12. X in an ordered pair (X, Y).
13. The mean of the x-values from the data set.
14. The mean of the y-values from the data set.
15. Can be used to test whether the correlation between two variables is significant.
16. The sum of squares of the differences between the y-value of each ordered pair and the mean of y. Also equal to the sum of the explained variation plus the unexplained variation.