Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.4 7.3 9.3 7.7 8.8 8.4 Weight (kg) 135 161 238 146 212 203 View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0 if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19 0.456 0.575 20 0.444 0.561 25 0.396 0.505 30 0.361 0.463 35 0.335 0.430 40 0.312 0.402 45 0.294 0.378 50 0.279 0.361 60 0.254 0.330 70 0.236 0.305 80 0.220 0.286 90 0.207 0.269 100 0.196 0.256 n α=0.05 α=0.01 The regression equation is y= __________+__________x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 1.7 cm is _______ kg. (Round to one decimal place as needed.)
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.4 7.3 9.3 7.7 8.8 8.4 Weight (kg) 135 161 238 146 212 203 View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0 if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19 0.456 0.575 20 0.444 0.561 25 0.396 0.505 30 0.361 0.463 35 0.335 0.430 40 0.312 0.402 45 0.294 0.378 50 0.279 0.361 60 0.254 0.330 70 0.236 0.305 80 0.220 0.286 90 0.207 0.269 100 0.196 0.256 n α=0.05 α=0.01 The regression equation is y= __________+__________x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 1.7 cm is _______ kg. (Round to one decimal place as needed.)
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
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Section 10.2
Question #10
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05.
|
Overhead Width (cm)
|
7.4
|
7.3
|
9.3
|
7.7
|
8.8
|
8.4
|
|
|---|---|---|---|---|---|---|---|
|
Weight (kg)
|
135
|
161
|
238
|
146
|
212
|
203
|
|
View the critical values of the Pearson correlation coefficient r.
Critical values of the pearson correlation coefficient r
|
n
|
α=0.05
|
α=0.01
|
NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0 if the absolute value of r is greater than the critical value in the table. |
|---|---|---|---|
|
4
|
0.950
|
0.990
|
|
|
5
|
0.878
|
0.959
|
|
|
6
|
0.811
|
0.917
|
|
|
7
|
0.754
|
0.875
|
|
|
8
|
0.707
|
0.834
|
|
|
9
|
0.666
|
0.798
|
|
|
10
|
0.632
|
0.765
|
|
|
11
|
0.602
|
0.735
|
|
|
12
|
0.576
|
0.708
|
|
|
13
|
0.553
|
0.684
|
|
|
14
|
0.532
|
0.661
|
|
|
15
|
0.514
|
0.641
|
|
|
16
|
0.497
|
0.623
|
|
|
17
|
0.482
|
0.606
|
|
|
18
|
0.468
|
0.590
|
|
|
19
|
0.456
|
0.575
|
|
|
20
|
0.444
|
0.561
|
|
|
25
|
0.396
|
0.505
|
|
|
30
|
0.361
|
0.463
|
|
|
35
|
0.335
|
0.430
|
|
|
40
|
0.312
|
0.402
|
|
|
45
|
0.294
|
0.378
|
|
|
50
|
0.279
|
0.361
|
|
|
60
|
0.254
|
0.330
|
|
|
70
|
0.236
|
0.305
|
|
|
80
|
0.220
|
0.286
|
|
|
90
|
0.207
|
0.269
|
|
|
100
|
0.196
|
0.256
|
|
|
n
|
α=0.05
|
α=0.01
|
The regression equation is y= __________+__________x.
(Round to one decimal place as needed.)
The best predicted weight for an overhead width of 1.7 cm is _______ kg.
(Round to one decimal place as needed.)
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