Each of the following graphs show the relationship between two variables. Determine the Pearson product-moment correlation coefficient (r) for each graph. 12 25- 10- n20- 8- 6- 15- 4 10- 2- 5- 0 0 20 0 10 20 Variable Variable Answer Bank r0.0 r0.8 r0.4 r 0.99 30- r0,9 oo 0.8- 20- 0.6- 0.4- 10- 0.2 0 5 10 0 15 0.2 0.4 0.6 0.8 10 Variable Variable Variable 3 Variable 6 Variable 8 Variable 5 30- 30 25- 25- 20- 20- 15- 15- 10- 10- 5- 5 10 15 5 10 15 Variable Variable 8- 2- 0 5 10 15 20 25 Variable Variable 2 Variable 7 Variable 4

Do a complete regression analysis using data below and find each item: a) Compute the value of the correlation coefficient. c) Use the Critical Value (CV) from the table to determine if there is a significant linear correlation. d) Determine the linear regression equation. e) Find the best predicted value.

A random sample of college students was surveyed about how they spend their time each week.  The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week.  The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows:             Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…

Which of the following is true about the correlation coefficient? A) It ranges from 0 to 1. B) It indicates the strength and direction of a linear relationship between two variables. C) It can be greater than 1. D) It is used to measure the central tendency of data.