The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight in braking distance on a dry surface? Use a =0.01. Weight, x Variablity In braking distance, y E Click here to view a table of critical values for Student's t-distribution. 5960 5330 6500 5100 5840 4800 P O Data Table 1.72 1.95 1.88 1.56 1.66 1.50 confidence, C 0.50 0.80 0.90 0.95 0.98 0.99 One tail, a 0.25 0.10 0.05 0.025 0.01 0.005 Setup the hypothesis for the test. d.f. . Two talls, a 0.50 0.20 0.10 0.05 0.02 0.01 6.314 12.706 31.821 63.657 6.965 1.000 3.078 Ho: P 1 0.816 1.886 2.920 4.303 9.925 Ha:p o 0.765 1.638 2.353 3.182 4.541 5.841 1.533 2.132 2.776 3.747 4.604 Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) 0.741 0.727 1.476 2.015 2.571 3.365 4.032 0.718 1.440 1.943 2.447 3.143 3.707 0.711 1.415 1.895 2.365 2.998 3.499 O A. The critical value is 0.706 1.397 1.860 2.306 2.896 3.355 0.703 1.383 1.833 2.262 2.821 3.250 O B. The critical values are - to -and to= 0,700 1.372 1.812 2.228 2.764 3.169 0.697 1.363 1.796 2.201 2.718 3.106 Calculate the test statistic. t- (Round to three decimal places as needed.) Print Done What is your conclusion? V a significant linear correlation between vehidle weight and variability in braking distance on a dry surface. There Venough evidence at the 1% level of significance to conclude that there
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight in braking distance on a dry surface? Use a =0.01. Weight, x Variablity In braking distance, y E Click here to view a table of critical values for Student's t-distribution. 5960 5330 6500 5100 5840 4800 P O Data Table 1.72 1.95 1.88 1.56 1.66 1.50 confidence, C 0.50 0.80 0.90 0.95 0.98 0.99 One tail, a 0.25 0.10 0.05 0.025 0.01 0.005 Setup the hypothesis for the test. d.f. . Two talls, a 0.50 0.20 0.10 0.05 0.02 0.01 6.314 12.706 31.821 63.657 6.965 1.000 3.078 Ho: P 1 0.816 1.886 2.920 4.303 9.925 Ha:p o 0.765 1.638 2.353 3.182 4.541 5.841 1.533 2.132 2.776 3.747 4.604 Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) 0.741 0.727 1.476 2.015 2.571 3.365 4.032 0.718 1.440 1.943 2.447 3.143 3.707 0.711 1.415 1.895 2.365 2.998 3.499 O A. The critical value is 0.706 1.397 1.860 2.306 2.896 3.355 0.703 1.383 1.833 2.262 2.821 3.250 O B. The critical values are - to -and to= 0,700 1.372 1.812 2.228 2.764 3.169 0.697 1.363 1.796 2.201 2.718 3.106 Calculate the test statistic. t- (Round to three decimal places as needed.) Print Done What is your conclusion? V a significant linear correlation between vehidle weight and variability in braking distance on a dry surface. There Venough evidence at the 1% level of significance to conclude that there
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Linear Correlation
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Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Question
Transcribed Image Text:The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability
in braking distance on a dry surface? Use a =0.01
Weight, x
Varlablity In
braking distance, y
5960 5330
6500
5100
5840
4800
Data Table
1.72
1.95
1.88
1.56
1.66
1.50
E Click here to view a table of critical values for Student's t-distribution
confidence, C0.50
0.80
0.90
0.95
0.98
0.99
One tail, a
0.25
0.10
0.05
0.025
0.01
0.005
Setup the hypothesis for the test.
d.f.
Two tails, a
0.50
0.20
0.10
0.05
0.02
0.01
Vo
10
12.706 31.821 63.657
1
1.000 3.078
6.314
Ho: p
0.816
1,886
2.920 4.303
6.965
9.925
Ha: pMo
0.765
1.638
2.353
3.182
5.841
4.541
0.741
1.533
2.132
2.776
3.747
4.604
Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice.
(Round to three decimal places as needed.)
0.727
1.476
2.015
2.571
3.365
4.032
0.718
1.440
1.943
2.447
3.143
3.707
0.711
1.415
1.895
2.365
2.998
3.499
O A. The critical value is.
0.706
1.397
1.860
2.306
2.896
3.355
B. The critical values are - to =
= and to =
0.703
1.383
1.833
2.262
2.821
3.250
10
0,700
1.372
1.812
2.228
2.764
3.169
0.697
1.363
1.796
2.201
2.718
3.106
Calculate the test statistic.
t= (Round to three decimal places as needed.)
Print
Done
What is your conclusion?
a significant linear correlation between vehicle weight and variability in braking distance on a dry surface.
There
V enough evidence at the 1% level of significance to conclude that there
Transcribed Image Text:I. Chi
Diana Vasqu
Tim
5 of 9 (4 complete) ▼
i Data Table
when stop
bet
0.718
1.440
1.943
2.447
3.143
3.707
7
0.711
1.415
1.895
2.365
2.998
3.499
0.706
1.397 1.860
2.306
2.896
3.355
0.703
1.383
1.833
2.262
2.821
3.250
2.228 2.764
2.718
10
0.700
1.372 1.812
3.169
11
0.697
1.363
1.796
2.201
3.106
3.055
3.012
12
0.695
1.356
1.782
2.179
2.681
13
0.694
1.350
1.771
2.160
2.650
14
0.692
1.345
1.761
2.145
2.624
2.977
15
0.691
1.341
1.753
2.131
2.602
2.947
16
0.690
1.337
1.746
2.120
2.583
2.921.
within your c
17
0.689
1.333
1.740
2.110
2.567
2.898
18
0.688
1.330
1.734
2.101
2.552
2.878
19
0.688
1.328
1.729
2.093
2.539
2.861
20
0.687
1.325
1.725
2.086
2.528
2.845
21
0.686
1.323
1.721
2.080
2.518
2.831
22
0.686
1.321
1.717
2.074
2.508
2.819
23
0.685
1.319
1.714
2.069
2.500
2.807
2.492
2.485
24
0.685
1.318
1.711
2.064
2.797
25
0.684
1.316
1.708
2.060
2.787
26
0.684
1.315 1.706
2.056
2.479
2.779
2.473
2.467
2.462
2.326
27
0.684
1.314
1.703
2.052
2.771
28
0.683
1.313
1.701
2.048
2.763
a signif
1.311
2.045
2.756
29
0.683
1.699
0.674
1.282
1.645
1.960
2.576
00
Print
Done
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