Applying the Concepts and SkillsIn Exercises, we repeat data from exercises in Section 14.2. For each exercise here,a. obtain the linear correlation coefficient.b. interpret the value of r in terms of the linear relationship between the two variables in question.c. discuss the graphical interpretation of the value of r and verify that it is consistent with the graph you obtained in the corresponding exercise in Section 14.2.d. square r and compare the result with the value of the coefficient of determination you obtained in the corresponding exercise in Section 14.3.Plant Emissions. Following are the data on plant weight and quantity of volatile emissions from Exercises 14.61 and 14.101. x 57 85 57 65 52 67 62 80 77 53 68 y 8.0 22.0 10.5 22.5 12.0 11.5 7.5 13.0 16.5 21.0 12.0

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…

Use the data in the table, which shows the average annual salaries (both in thousands of dollars) for public school principals and teachers in the U.S. for 11 years. Apply what you have learned in the previous tab to complete this graded lab questions. 1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the corelation coefficient is R and not R Teachers y Principalsx 77.8 43.7 78.4 43.8 80.8 45.0 R= 80.5 45.6, 2. Does the R value represent a positive, negative or no correlation between the salaries ol the teachers and principals? As teacher salaries increase, what happens to prinicipal salaries? 10 11 81.5 45.9 84.8 48.2 12 13 87.7 49,3 3. Write the equation of the regression line for the data below. The equation is y= 14 91.6 51.3 52.9 Teachers y 15 16 95.7 54.4 COD 54.2 =D0.5873x-2.0s07o R=0.995, 17 95.7 4. Use the regression equation that you found in exercise #3 to predict the average annual salary…

What kind of relationship is depicted in the following graph? 7 2 1 0 2 3 a. A positive linear correlation b. A nonlinear correlation c. No correlation Od. A negative linear correlation 6 9 10