Consider the four data sets shown in the accompanying table. Complete parts (a) and (b) below.Click the icon to view the data table.(a) Compute the linear correlation coefficient for each data set.The linear correlation coefficient for the first data set is(Round to three decimal places as needed.)The linear correlation coefficient for the second data set is(Round to three decimal places as needed.)The linear correlation coefficient for the third data set is(Round to three decimal places as needed.)The linear correlation coefficient for the fourth data set is(Round to three decimal places as needed.)(b) Draw a scatter diagram for each data set. Conclude that linear correlation coefficients and scatter diagrams must be used together in any statistical analysis of bivariate data.Draw a scatter diagram for the first data set. Choose the correct graph below.OA.Ay15+OA.Draw a scatter diagram for the second data set. Choose the correct graph below.0OA.PA0QQDraw a scatter diagram for the third data set. Choose the correct graph below.15-QQDraw a scatter diagram for the fourth data set. Choose the correct graph below.OA.B.15OB.15+0OB.Ay15-0OB.20+0wwwQCQGQGCOC.O C.15+OC.Ay15OC.15-04GQQO D.Ay15+OD.Ay15+0OD.15-0OD.15-✓ ✓QQ x110813911146412SLE75y110.048.959.5810.81x210813910.33 1111.96 149.24 6Lo st6.26412.84126.82 77.68 5y211.1410.1410.7410.7711.2610.108.135.1011.139.2676.47 5x3108139111464412y39.468.7714.749.119.8110.848.087.39x478.427.73777777710.15 7718y48.587.769.7110.8410.479.047.257.569.918.8914.50

Given information: x1 y1 x2 y2 x3 y3 x4 y4 10 10.04 10 11.14 10 9.46 7 8.58 8 8.95 8 10.14 8…

Answered: Consider the four data sets shown in…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Complete the following objectives for each data set:(a) Draw a scatter plot(b) Estimate the correlation in words (positive, negative, or no correlation)(c) Calculate the correlation coefficient, r.(d) Determine whether r is statistically significant at the 0.01 level of significance.(e) Determine whether r is statistically significant at the 0.05 level of significance.(f) Calculate the coefficient of determination, r2.(g) Interpret the meaning of r2 for the given set of data. (f) Find the equation of the least-squares regression line, if appropriate. The following table contains data from 16 former elementary statistics students, where x represents the number of absences a student had for the semester and y represents the student’s final class average. Absences Class Average 2 86 2 83 3 81 10 53 3 92 7 71 9 68 1 79 12 53 9 78 1 77 1 85 13 62 1 97 10 54 3 79
I need correlation coefficient ,test statistic , p value & conclusion pls help I need in an hour
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Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day. a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?
Does a major league baseball team's record during spring training indicate how the team will play during the regular season? Over a six-year period, the correlation coefficient between a team's winning percentage in spring training and its winning percentage in the regular season is . Shown are the winning percentages for the American League teams during a season. Team SpringTraining RegularSeason Team SpringTraining RegularSeason Baltimore Orioles 0.409 0.424 Minnesota Twins 0.492 0.542 Boston Red Sox 0.426 0.588 New York Yankees 0.579 0.559 Chicago White Sox 0.411 0.535 Oakland A's 0.690 0.468 Cleveland Indians 0.578 0.492 Seattle Mariners 0.492 0.379 Detroit Tigers 0.578 0.459 Tampa Bay Rays 0.722 0.601 Kansas City Royals 0.540 0.461 Texas Rangers 0.640 0.491 Los Angeles Angels 0.724 0.619 Toronto Blue Jays 0.442 0.533 a. What is the correlation coefficient between the spring training and the regular season winning percentages…
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 =
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Give an example of two variables that have a positive linear correlation. Give an example of two variables that have a negative linear correlation. Give an example of two variables that have no correlation. Below is the height in inches and weight in pounds of eleven individuals Height, x 62 63 66 68 70 72 73 74 74 75 75 Weight, y 195 190 250 220 250 255 260 275 280 295 300 x = 65 inches x = 69 inches x = 71 inches
The data below shows the selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold. Construct a scatterplot, find the value of the linear correlation coefficient r, and P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between the two variables? Selling Price (x) List Price (y) H₁: p#0 400 412 Construct a scatterplot. Choose the correct graph below. 301 315 376 387 434 440 459 488 H₁ p > 0 477 480 319 324 352 368 417 434 330 341
Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(0,7),(1,5),(1.5,3),(2,5),(2.3,3.2),(3,2),(3.5,4)}{(0,7),(1,5),(1.5,3),(2,5),(2.3,3.2),(3,2),(3.5,4)} The regression line is: y=y= Answer −− Answer xx Based on the regression line, we would expect the value of response variable to be Answer when the explanatory variable is 0. (NOTE: This is the yy-intercept.) For each increase of 1 in of the explanatory variable, we can expect a(n) Answerdecreaseincrease of Answer in the response variable. (NOTE: This is the slope.) If x=2.5x=2.5, the yˆ=y^= Answer. This is an example of Answerextrapolationinterpolation. The correlation coefficient is r=r= Answer.
Answer

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