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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 272.8 mm. How does the result compare to the actual height of 1776 mm? Foot Length Height 281.8 277.7 253.2 259.2 279.1 258.0 274.2 262.2 e 1784.7 1770.8 1676.3 1645.8 1858.9 1709.7 1789.3 1737.2 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 272.8 mm is mm. (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? O A. The result is close to the actual height of 1776 mm. O B. The result is exactly the same as the actual height of 1776 mm. OC. The result is very different from the actual height of 1776 mm. OD. The result does not make sense given the context of the data.

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 272.8 mm. How does the result compare to the actual height of 1776 mm? Foot Length Height 281.8 277.7 253.2 259.2 279.1 258.0 274.2 262.2 e 1784.7 1770.8 1676.3 1645.8 1858.9 1709.7 1789.3 1737.2 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 272.8 mm is mm. (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? O A. The result is close to the actual height of 1776 mm. O B. The result is exactly the same as the actual height of 1776 mm. OC. The result is very different from the actual height of 1776 mm. OD. The result does not make sense given the context of the data.

A First Course in Probability (10th Edition)
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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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 272.8 mm. How does the result compare to the actual height of 1776 mm? Foot Length 281.8 277.7 253.2 259.2 279.1 258.0 274.2 262.2 D Height 1784.7 1770.8 1676.3 1645.8 1858.9 1709.7 1789.3 1737.2 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 272.8 mm is mm. (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? A. The result is close to the actual height of 1776 mm. B. The result is exactly the same as the actual height of 1776 mm. C. The result is very different from the actual height of 1776 mm. D. The result does not make sense given the context of the data.
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 272.8 mm. How does the result compare to the actual height of 1776 mm? Foot Length 281.8 277.7 253.2 259.2 279.1 258.0 274.2 262.2 D Height 1784.7 1770.8 1676.3 1645.8 1858.9 1709.7 1789.3 1737.2 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 272.8 mm is mm. (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? A. The result is close to the actual height of 1776 mm. B. The result is exactly the same as the actual height of 1776 mm. C. The result is very different from the actual height of 1776 mm. D. The result does not make sense given the context of the data.
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