The sum of the squared residuals for the line contalning the points (- 2, - 2) and (2,5) is 0.875(d) Compute the sum of the squared residuals of the given data set for the least-squares regression line found in part (a).The sum of the squared residuals for the least-squares regression line is Consider the data set given in the accompanying table. Complete parts (a) through (dE Click the icon to view the data table.Data Table(a) Determine the least-squares regression line. Choose the correct answer below.- 2- 112A. The least-squares regression line is y = 1.8x + 1.6.y- 214O B. The least-squares regression line is y = 1.6x + 1.8.O C. The least-squares regression line is y = 1.5x + 1.75.O D. The least-squares regression line is y = 1.8x + 1.75.PrintDone

The sum of the squared residuals for the least squares regression line is ?

Answered: (d) Compute the sum of the squared…

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

18th Edition

ISBN:9780079039897

Author:Carter

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Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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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?
The least squares regression line for a set of data is calculated to be y = 24.8 + 3.41x. (a) One of the points in the data set is (4, 37). Calculate the predicted value. (b) For the point in part (a), calculate the residual.
Interpret the least squares regression line of this data set. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The correct least squares regression line for the data set is: y = 8.116x + 273.273 Use it to complete the following sentence: The least squares regression line predicts an additional annual rainfall if the average temperature of coastal waters increases by one degree millimetres of Celsius.
Find the equation for the least squares regression line of the data described below. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. Round your answers to the nearest thousandth. y = L Submit
A regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The least squares regression line is weight = -5.94 + 0.1875 length. Explain in words what this model means (slop and intercept) The new- born boy was 48 cm long, what is the predicted weight of this boy? It is known that the boy is weighed 3 kg. what was his residual? What does that say about him?
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the National League teams in the year 2002 . The variable x denotes the player payroll (in millions of dollars) for the year 2002 , and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in Figure 1 scatter plot, as is the least-squares regression line. The equation for this line is =y+5.910.34x . Answer the following: 1. Fill in the blank: For these data, mean attendance values that are less than the mean of the mean attendance values tend to be paired with player payroll values that are _____ the mean of the player payroll values. Choose onegreater thanless than 2. Fill in the blank: According to the regression equation, for an increase of one million dollars in player payroll, there is a corresponding _____ of 0.34 thousand fans in mean attendance. Choose…
Use the least squares regression line of this data set to predict a value. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The least squares regression line of this data set is: y = 8.116x + 273.273 How much rainfall does this line predict in a year if the average temperature of coastal waters is 15 degrees Celsius? Round your answer to the nearest integer. millimetres
A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.69 + 0.1656 length. A newborn was 48cm long and weighed 33kg. According to the regression model, what was his residual? What does that say about him?
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Compute the least-squares regression line for predicting the right foot temperature from the left foot temperature. Round the slope and y-intercept values to four decimal places.
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A recent study showed that the hours a person exercised in a week affected the individual'sresting heart rate. It was computed that r = -.68 and the least squares regression line was?̂ = 83-1.4x, where x is the hours exercised and y is the resting heart rate. d. What percentage of variability in resting heart rate can be explained by variability inhours exercised?

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(d) Compute the sum of the squared residuals of the given data set for the least-squares regression line found in part (a). The sum of the squared residuals for the least-squares regression line is