Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 160 170 120 130 90 180 Sodium, y 415 465 340 370 250 510 The equation of the regression line is ŷ = ______ x + ______ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) x = 180 calories, (b) x = 100 calories, (c) x = 140 calories, (d) x = 220 calories Use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) Substitute x = 180 into the regression equation and simplify. (b) Substitute x = 100 into the regression equation and simplify. (c) Substitute x = 140 into the regression equation and simplify. (d) Substitute x = 220 into the regression equation and simplify.
Find the equation of the regression line for the given data. Then construct a
Calories, x
|
160 |
170 |
120 |
130 |
90 |
180 |
Sodium, y
|
415 |
465 |
340 |
370 |
250 |
510 |
The equation of the regression line is ŷ = ______ x + ______
(Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
(a) x = 180 calories, (b) x = 100 calories, (c) x = 140 calories, (d) x = 220 calories
Use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not.
(Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
(a) Substitute x = 180 into the regression equation and simplify.
(b) Substitute x = 100 into the regression equation and simplify.
(c) Substitute x = 140 into the regression equation and simplify.
(d) Substitute x = 220 into the regression equation and simplify.
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