X |
Y |
XY |
X² |
Y² |
30 |
2.85 |
85.5 |
900 |
8.1225 |
50 |
6.50 |
325 |
2500 |
42.25 |
34 |
1.50 |
51 |
1156 |
2.25 |
12 |
6.35 |
76.2 |
144 |
40.3225 |
37 |
6.20 |
229.4 |
1369 |
38.44 |
33 |
6.75 |
222.75 |
1089 |
45.5625 |
36 |
3.60 |
129.6 |
1296 |
12.96 |
26 |
6.10 |
158.6 |
676 |
37.21 |
18 |
8.35 |
150.3 |
324 |
69.7225 |
46 |
4.35 |
200.1 |
2116 |
18.9225 |
∑X=322 |
∑Y=52.55 |
∑XY=1628.45 |
ΣX² =11570 |
∑Y2 =315.7625 |
r = COV(X,Y)/σXσY
= (1628.45/10)-(322/10)(52.55/10)/√(11570/10)-(322/10)2√(315.7625/10)-(52.55/10)2
= (162.845-169.211)/√(1157-1036.84)√(31.57625-27.615025)
= -6.366/(10.961)(3.9612)
= -0.146
b)
n = 10 and α = 0.05
Null hypothesis H0: P=0
Alternative hypothesis H1: p ≠ 0
t(α/2,n-2) =±2.30
c)
tcal = -0.146√10-2/√1-(-0.146)2 = -0.4174
d) tcal = -0.4174 lies between the critical value ±2.30
NO,do not reject the null hypothesis of linear relation
Using the data given in the table below, answer the following questions. (Round your final answers...
Using the data given in the table below, answer the following questions. (Round your final answers to 3 decimal places.) Order Size and Shipping Cost (n 12) Ship Cost (Y) 4,489 5,611 3,290 4,113 4,883 5,425 4,414 5,506 3,346 3,673 6,542 5,088 Orders (X) 1,068 1,026 767 885 1,156 1,146 892 938 769 677 1,174 1,009 Click here for the Excel Data File (a) Use Excel, MegaStat, or MINITAB to calculate the correlation coefficient. calc (b)Use Excel or Appendix D...
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