Rice prices in the market are largely affected by grain quality traits. One of the grain quality traits commonly used in early breeding programs is amylose content. A rice sample that has no amylose is classified as sticky rice. A rice grain quality laboratory wishes to adopt a new method for the analysis of amylose content. Use a paired Student's t-test to determine if the new and old analysis procedures are giving the same results at the 95% confidence level. SAMPLE OLD 1 2 NEW 9.4 23.4 10.5 27.4
Rice prices in the market are largely affected by grain quality traits. One of the grain quality traits commonly used in early breeding programs is amylose content. A rice sample that has no amylose is classified as sticky rice. A rice grain quality laboratory wishes to adopt a new method for the analysis of amylose content. Use a paired Student's t-test to determine if the new and old analysis procedures are giving the same results at the 95% confidence level. SAMPLE OLD 1 2 NEW 9.4 23.4 10.5 27.4
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Transcribed Image Text:Rice prices in the market are largely affected by grain
quality traits. One of the grain quality traits commonly
used in early breeding programs is amylose content. A
rice sample that has no amylose is classified as sticky
rice. A rice grain quality laboratory wishes to adopt a
new method for the analysis of amylose content. Use a
paired Student's t-test to determine if the new and old
analysis procedures are giving the same results at the
95% confidence level.
SAMPLE
OLD
1
2
3
4
5
6
7
8
NEW
9.4
23.4
14.2
32.1
9.2
21.7
21.4
13.5
10.5
27.4
15.6
32.9
7.8
22.9
26.9
18.8
Transcribed Image Text:Use the table below for the Student's t test values.
Degrees
of
freedom
1
2
345
6
7
8
9
10
20%
(0.20)
3.078
1.886
1.638
1.533
1.476
1.440
1.415
1.397
1.383
1.372
10%
(0.10)
6.314
2.920
2.353
2.132
2.015
1.943
1.895
1.860
1.833
1.812
Significance level
5%
2%
(0.05) (0.02)
1%
(0.01)
12.706 31.821 63.657
4.303
6.965
9.925
3.182 4.541
5.841
2.776 3.747
4.604
2.571 3.365
4.032
2.447
3.143
2.365 2.998
2.306 2.896
2.262
2.821
2.228
2.764
3.707
3.499
3.355
3.250
3.169
0.1%
(0.001)
636.619
31.598
12.941
8.610
6.859
5.959
5.405
5.041
4.781
4.587
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