6. Two separate tests are designed to measure a student's ability to solve problems. Several students are randomly selected to take both tests and the results are given below. (x)TestA 48 52 58 44 43 43 40 51 59 (y)TestB| 73 67 73 59 58 56 58 64 74 a. Plot the scatter diagram below. Label x and y axes. Do a rough sketch. b. Find the value of the linear correlation coefficient r by the TI83 shortcut- state calculator screen name c) Test the claim of no linear relation by the TI83 p-value method. a .05 claim null hypothesis. alternative hypothesis... Calculator Screen Name..... test statistic pvalue/alpha comparison.….... decision Conclusion d) Find the estimated equation of the regression line by T183 shortcut e) Plot the regression line on the scatter diagram in part a). f) Assuming a significant linear correlation, predict the score a student would get on Test B, given he got a 90 on Test A. g) What percentage of the total variation can be explained by the regression line

The numbers of pass attempts and passing yards for seven professional quarterback for a recent year are listed in the table below. Round all answers to the nearest 1000th. Pass attempts (x) 449 565 528 197 670 351 218 Passing Yards (y) 3265 4018 3669 1141 5177 2362 1737   Calculate the sample correlation coefficient, r.     Describe the type of correlation coefficient and interpret the correlation in the context of the data.             Find the equation of the regression line for the data.       Use the regression equation to predict the average number passing yards if the pass attempts are 250.

The data below is 12 observations of Math SAT scores (x) and scores on Math placement test (y). Calculate the linear correlation coefficient, rr. Enter your answers to two decimal places. X Y 420 426 410 360 600 575 460 538 550 553 480 407 560 635 450 388 400 383 430 402 470 462 440 437 rr =

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…

A local store kept track of the number of advertisements it placed in local newspapers and the number of stereo systems it sold each week. Week 1 2 3 4 5 6 7 8 Advertisements, x 7 5 4 2 8 5 5 3 Stereos Sold, y 23 15 12 8 2 7 9 6 a) Create a scatter plot for the data showing Advertisements Vs. Stereos Sold. b) Determine the value of r, the correlation coefficient for the set of data and classify the type of correlation. c) What does this correlation coefficient suggest about the effectiveness of the advertisements? Explain

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