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 2.4 cm. 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) Weight (kg) 7.8 7.1 9.5 9.8 8.5 7.2 161 161 259 246 212 161 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x (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 2.4 cm. 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) Weight (kg) 7.8 7.1 9.5 9.8 8.5 7.2 161 161 259 246 212 161 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x (Round to one decimal place as needed.)
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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Transcribed Image Text: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 2.4 cm. 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)
Weight (kg)
8.5
212
7.8
7.1
9.5
9.8
7.2
161
161
259
246
161
Click the icon to view the critical values of the Pearson correlation coefficient r.
The regression equation is y =+x.
(Round to one decimal place as needed.)
Transcribed Image Text:954
0.2.2
Critical Values of the Pearson Correlation Coefficient r
0.004
14
16
17
18
19
20
25
30
35
40
45
50
60
70
80
90
100
0.532
0.514
0.497
0.482
0.468
0.456
0.444
0.396
0.361
0.335
0.312
0.294
0.279
0.254
0.236
0.220
0.207
0.196
0.661
0.641
0.623
0.606
0.590
0.575
0.561
0.505
0.463
0.430
0.402
0.378
0.361
0.330
0.305
0.286
0.269
0.256
a= 0.05
a=0.01
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