Use the given data set to complete parts (a) through (c) below. (Use α = 0.05.) X y 10 9.14 8 8.15 13 8.75 9 8.76 Click here to view a table of critical values for the correlation coefficient. 4 8 12 16 4 8 12 16 11 9.27 14 8.11 6 6.13 4 3.09 12 9.13 7 7.27 5 4.74 4 8 12 16 04 8 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r = 0.816. (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. OA. There is insufficient evidence to support the claim of a linear correlation between the two variables. B. There is sufficient evidence to support the claim of a linear correlation between the two variables. OC. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. OD. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables. c. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below. OA. The scatterplot reveals a distinct pattern that is not a straight-line pattern. OB. The scatterplot does not reveal a distinct pattern. OC. The scatterplot reveals a distinct pattern that is a straight-line pattern with negative slope. OD. The scatterplot reveals a distinct pattern that is a straight-line pattern with positive slope. Table of Critical Values n a = .05 a = .01 4 .950 .990 5 .878 .959 6 .811 .917 7 .754 .875 8 .707 .834 9 .666 .798 10 .632 .765 11 .602 .735 12 .576 .708 13 .553 .684 14 .532 .661 15 .514 .641 16 .497 .623 17 .482 .606 18 .468 .590 19 .456 .575 20 .444 .561 25 .396 .505 30 .361 .463 35 .335 .430 40 .312 .402 45 .294 .378 50 .279 .361 60 .254 .330 70 236 .305 80 220 286 90 .207 .269 100 196 256 NOTE: To test Hop = 0 against H: p = 0, reject Ho if the absolute value of r is greater than the critical value in the table.
Use the given data set to complete parts (a) through (c) below. (Use α = 0.05.) X y 10 9.14 8 8.15 13 8.75 9 8.76 Click here to view a table of critical values for the correlation coefficient. 4 8 12 16 4 8 12 16 11 9.27 14 8.11 6 6.13 4 3.09 12 9.13 7 7.27 5 4.74 4 8 12 16 04 8 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r = 0.816. (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. OA. There is insufficient evidence to support the claim of a linear correlation between the two variables. B. There is sufficient evidence to support the claim of a linear correlation between the two variables. OC. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. OD. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables. c. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below. OA. The scatterplot reveals a distinct pattern that is not a straight-line pattern. OB. The scatterplot does not reveal a distinct pattern. OC. The scatterplot reveals a distinct pattern that is a straight-line pattern with negative slope. OD. The scatterplot reveals a distinct pattern that is a straight-line pattern with positive slope. Table of Critical Values n a = .05 a = .01 4 .950 .990 5 .878 .959 6 .811 .917 7 .754 .875 8 .707 .834 9 .666 .798 10 .632 .765 11 .602 .735 12 .576 .708 13 .553 .684 14 .532 .661 15 .514 .641 16 .497 .623 17 .482 .606 18 .468 .590 19 .456 .575 20 .444 .561 25 .396 .505 30 .361 .463 35 .335 .430 40 .312 .402 45 .294 .378 50 .279 .361 60 .254 .330 70 236 .305 80 220 286 90 .207 .269 100 196 256 NOTE: To test Hop = 0 against H: p = 0, reject Ho if the absolute value of r is greater than the critical value in the table.
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:Use the given data set to complete parts (a) through (c) below. (Use α = 0.05.)
X
y
10
9.14
8
8.15
13
8.75
9
8.76
Click here to view a table of critical values for the correlation coefficient.
4
8 12 16
4
8 12 16
11
9.27
14
8.11
6
6.13
4
3.09
12
9.13
7
7.27
5
4.74
4
8 12 16
04 8
12 16
b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.
The linear correlation coefficient is r = 0.816.
(Round to three decimal places as needed.)
Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the
correct answer below.
OA. There is insufficient evidence to support the claim of a linear correlation between the two variables.
B. There is sufficient evidence to support the claim of a linear correlation between the two variables.
OC. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables.
OD. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables.
c. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below.
OA. The scatterplot reveals a distinct pattern that is not a straight-line pattern.
OB. The scatterplot does not reveal a distinct pattern.
OC. The scatterplot reveals a distinct pattern that is a straight-line pattern with negative slope.
OD. The scatterplot reveals a distinct pattern that is a straight-line pattern with positive slope.
Transcribed Image Text:Table of Critical Values
n
a = .05
a = .01
4
.950
.990
5
.878
.959
6
.811
.917
7
.754
.875
8
.707
.834
9
.666
.798
10
.632
.765
11
.602
.735
12
.576
.708
13
.553
.684
14
.532
.661
15
.514
.641
16
.497
.623
17
.482
.606
18
.468
.590
19
.456
.575
20
.444
.561
25
.396
.505
30
.361
.463
35
.335
.430
40
.312
.402
45
.294
.378
50
.279
.361
60
.254
.330
70
236
.305
80
220
286
90
.207
.269
100
196
256
NOTE: To test Hop = 0 against H: p = 0,
reject Ho if the absolute value of r is
greater than the critical value in the table.
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