Question

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

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 2.5 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) 8.1 8.3 9.2 8.7 7.8 8.4 Weight (kg) 185 223 258 209 191 224 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is ĝ=+1x. (Round to one decimal place as needed.) kg. The best predicted weight for an overhead width of 2.5 cm is (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? O A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data OB. The prediction cannot be correct because a negative weight does not make sense and because there is not sufficient evidence of a linear correlation. O C. The prediction cannot be correct because there is not sufficient evidence of a linear correlation. The width in this case is beyond the scope of the available sample data OD. The prediction can be correct. There is nothing wrong with predicting the weight in this case.

Answer 1

Bookl - Microsoft Excel Chart Tools Home Insert Page Layout Formulas Data Review View Design Layout Format 2 do Change Save As Switch Select Chart Type Template Row/Column Data Type Data Chart 1 - fic Move Chart Location Chart Layouts Chart Styles A B С D E F H 1 J K L M N o Р 0 R S T U 1 X 2 185 3 223 y 4 TV 8.1 8.3 9.2 8.7 7.8 8.4 258 209 300 5 6 7 191 224 y = 46.452x - 175.97 R?=0.7314 250 8 9 200 10 11 12 Axis Title 150 13 y Linear (v) 14 15 100 16 17 18 50 19 20 0 21 22 7.6 7.8 8 8.2 8.4 8.6 8.8 9 9.2 9.4 Axis Title 23 24 25 + Sheet1 Sheet2 Sheet3 Ready D Average: 111.7083333 Count: 14 Sum: 1340.5 DO 100% +

Ho: Pro H, P0 Regressionen ŷ =-176 + 46.50 R?= 0.7314 &= 0.85S (-: Positive slope) Form=6, rcritical = et a=0.05 0.811 here, rrcritical !. reject Ho. :. corelation is significant. For C= 2,5, ģ= 176 + 46,5(2.5) R9 59.75 -59.8 what is wrong? A The prediction camnot be conect because anegative weight does not make sense. The width in this case is beyond the scope of The available scumple dretce. CS Scanned with CamScanner