Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.3 mm How does the result compare to the actual height of 1776 mm? Use a significance level of 0.05. Foot Length Height 281.9 277.8 252.9 259.2 278.7 258.2 274.2 262.3 1785.1 1770.7 1675.7 1646.3 1858.8 1709.8 1789.0 1737.0 The regression equation is y = + (x (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 273.3 mm is (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? OA. The result is very different from the actual height of 1776 mm. OB. The result is exactly the same as the actual height of 1776 mm. OC. The result is close to the actual height of 1776 mm. mm. OD. The result does not make sense given the context of the data. E
Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.3 mm How does the result compare to the actual height of 1776 mm? Use a significance level of 0.05. Foot Length Height 281.9 277.8 252.9 259.2 278.7 258.2 274.2 262.3 1785.1 1770.7 1675.7 1646.3 1858.8 1709.8 1789.0 1737.0 The regression equation is y = + (x (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 273.3 mm is (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? OA. The result is very different from the actual height of 1776 mm. OB. The result is exactly the same as the actual height of 1776 mm. OC. The result is close to the actual height of 1776 mm. mm. OD. The result does not make sense given the context of the data. E
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 4GP
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Transcribed Image Text:Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.3 mm
How does the result compare to the actual height of 1776 mm? Use a significance level of 0.05.
Foot Length
Height
281.9 277.8 252.9 259.2 278.7 258.2 274.2 262.3
1785.1 1770.7 1675.7 1646.3 1858.8 1709.8 1789.0 1737.0
The regression equation is y = + (x
(Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.)
The best predicted height of a male with a foot length of 273.3 mm is
(Round to the nearest integer as needed.)
How does the result compare to the actual height of 1776 mm?
OA. The result is very different from the actual height of 1776 mm.
OB. The result is exactly the same as the actual height of 1776 mm.
OC. The result is close to the actual height of 1776 mm.
mm.
OD. The result does not make sense given the context of the data.
E
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