Like father, like son: In 1906, the statistician Karl Pearson measured the heights of 1078 pairs of fathers and sons. The following table presents a sample of 8 pairs, with height measured in inches, simulated from the distribution specified by Pearson. Father's Son's height height 65.4 66.0 65.7 70.9 66.7 68.8 70.1 73.3 72.4 69.1 65.7 65.3 72.3 71.9 73.6 76.5 Send data to Excel The least-squares regression line y=bo+b₁x=16.1867+0.7833x and Σ (x-x)² = 84.8487 are known for these data. Use the P-value method to test H: B₁=0 versus H₁: B₁ +0. Can you conclude that father's height is useful in predicting son's height? Use the a=0.10 level of significance. Part: 0 / 4 Part 1 of 4 Compute the test statistic. Always round -score values to three decimal places.
Like father, like son: In 1906, the statistician Karl Pearson measured the heights of 1078 pairs of fathers and sons. The following table presents a sample of 8 pairs, with height measured in inches, simulated from the distribution specified by Pearson. Father's Son's height height 65.4 66.0 65.7 70.9 66.7 68.8 70.1 73.3 72.4 69.1 65.7 65.3 72.3 71.9 73.6 76.5 Send data to Excel The least-squares regression line y=bo+b₁x=16.1867+0.7833x and Σ (x-x)² = 84.8487 are known for these data. Use the P-value method to test H: B₁=0 versus H₁: B₁ +0. Can you conclude that father's height is useful in predicting son's height? Use the a=0.10 level of significance. Part: 0 / 4 Part 1 of 4 Compute the test statistic. Always round -score values to three decimal places.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:Like father, like son: In 1906, the statistician Karl Pearson measured
the heights of 1078 pairs of fathers and sons. The following table presents
a sample of 8 pairs, with height measured in inches, simulated from the
distribution specified by Pearson.
Father's Son's
height height
65.4
66.0
65.7
70.9
66.7
68.8
70.1
73.3
72.4
69.1
65.7
65.3
72.3
71.9
73.6
76.5
Send data to Excel
= 84.8487
The least-squares regression line y=b+b₁x=16.1867 +0.7833x and Σ (x-x)² = 84
are known for these data. Use the P-value method to test H₁: B₁=0 versus
H₁: B₁ +0. Can you conclude that father's height is useful in predicting son's
height? Use the a=0.10 level of significance.
Part: 0/4
Part 1 of 4
Compute the test statistic. Always round -score values to three
decimal places.
X

Transcribed Image Text:Fast reactions: In a study of reaction times, the time to respond to a
visual stimulus (x) and the time to respond to an auditory stimulus (y)
were recorded for each of 6 subjects. Times were measured in
thousandths of a second. The results are presented in the following
table. The results are presented in the following table.
Visual
161
235
201
228
191
178
Send data to Excel
Auditory
159
241
197
209
169
201
Use the TI-84 calculator.
Part: 0 / 2
Part 1 of 2
Compute the least-squares regression line for predicting the time to
respond to an auditory (») from the time to respond to a visual
stimulus (x). Round the slope and y-intercept values to at least four
decimal places.
The regression equation is =.
X
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