CENGAGE | MINDTAPEnd-of-Chapter Problems: Chapter 14 Correlation and RegressionFor the following scores,X Y11135157685 9Compute SS for X and Y and SP.r =ΣΧΣΥCompute the Pearson correlation.(to two decimal places)ΣΧΥSSXMacBook ProSSYSPa Se

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Answered: IN ENGAGE End-of-Chapter Problems:…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

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Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Noise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.
Planetary Velocity The following table gives the mean velocity of planets in their orbits versus their mean distance from the sun. Note that 1AU astronomical unit is the mean distance from Earth to the sun, abut 93 million miles. Planet d=distance AU v=velocity km/sec Mercury 0.39 47.4 Venus 0.72 35.0 Earth 1.00 29.8 Mars 1.52 24.1 Jupiter 5.20 13.1 Saturn 9.58 9.7 Uranus 19.20 6.8 Neptune 30.05 5.4 Astronomers tell us that it is reasonable to model these data with a power function. a Use power regression to express velocity as a power function of distance from the sun. b Plot the data along with the regression equation. c An asteroid orbits at a mean distance of 3AU from the sun. According to the power model you found in part a, what is the mean orbital velocity of the asteroid?
5) Can i get help with this question please
The correlation coefficient between midterm and final scores in a large statistics class is r=0.6. A scatterplot of the two variables is football shaped. A particular student has a midterm score that is 0.5 SDs below the average midterm score of all students. Using regression, we would predict that the student's final score is _________ SDs _________ the average final score of all students and therefore at the _________ percentile of final scores of all students.
Please help me with question d, e, f, g, h, and I. Thank you.

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IN ENGAGE End-of-Chapter Problems: Chapter 14 Correlation and Regression For the following scores, X 11 3 5 6 5 r = Y 1 15 Compute SS for X and Y and SP. ΣΧ 7 8 9 ΣΥ Compute the Pearson correlation. (to two decimal places) ΣΧΥ SSX MacBook Pro SSY SP a s