A pilot study on three-member wood joints held with a single steel bolt was performed to determine if previous loadconditions affected the strength of the joints. Four different pre-load conditions were applied over the course of a full year,but all other factors were kept the same (all joints were made to the same design from Douglas-fir).Destructive testing then determined the strengths of the joints by monitoring the maximum load (pounds) to joint failure.The data for the four load conditions is shown in the table below.Pre-load ConditionАВCDNo-load | 2.04 tons1.44 tons | 0.72 tons2.212.972.572.412.292.332.512.692.32.912.432.742.322.432.462.772.222.252.783.292.432.792.553.12.312.543.712.512.9Carry out a one-way ANOVA, and test at a 5% level of significance whether any of the pre-load condition variants areassociated with differences in strength. State and explain your conclusion. Explain how you reached your conclusion.Compute and report the p-value of your observed statistic.Carry out a multiple-comparison analysis to determine which, if any, of the four pre-load conditions are significantlydifferent from each other in their resulting strength.What assumptions are necessary for the ANOVA to be valid? Do these assumptions seem to be satisfied by this particularset of data? Explain your answer.

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A pilot study on three-member wood joints held with a single steel bolt was performed to determine if previous load conditions affected the strength of the joints. Four different pre-load conditions were applied over the course of a full year, but all other factors were kept the same (all joints were made to the same design from Douglas-fir). Destructive testing then determined the strengths of the joints by monitoring the maximum load (pounds) to joint failure. The data for the four load conditions is shown in the table below. Pre-load Condition А В C No-load | 2.04 tons 1.44 tons 0.72 tons 2.21 2.97 2.57 2.41 2.29 2.33 2.51 2.69 2.3 2.91 2.43 2.74 2.32 2.43 2.46 2.77 2.22 2.25 2.78 3.29 2.43 2.79 2.55 3.1

A pilot study on three-member wood joints held with a single steel bolt was performed to determine if previous load conditions affected the strength of the joints. Four different pre-load conditions were applied over the course of a full year, but all other factors were kept the same (all joints were made to the same design from Douglas-fir). Destructive testing then determined the strengths of the joints by monitoring the maximum load (pounds) to joint failure. The data for the four load conditions is shown in the table below. Pre-load Condition А В C No-load | 2.04 tons 1.44 tons 0.72 tons 2.21 2.97 2.57 2.41 2.29 2.33 2.51 2.69 2.3 2.91 2.43 2.74 2.32 2.43 2.46 2.77 2.22 2.25 2.78 3.29 2.43 2.79 2.55 3.1

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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2-Proportion Test

In a 2-proportion test, two separate proportions are measured at the same time, and their similarity is evaluated. It is also known as a 2-proportion z-test, and a comparison of two different proportions is done in this method.

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A pilot study on three-member wood joints held with a single steel bolt was performed to determine if previous load
conditions affected the strength of the joints. Four different pre-load conditions were applied over the course of a full year,
but all other factors were kept the same (all joints were made to the same design from Douglas-fir).
Destructive testing then determined the strengths of the joints by monitoring the maximum load (pounds) to joint failure.
The data for the four load conditions is shown in the table below.
Pre-load Condition
А
В
C
D
No-load | 2.04 tons
1.44 tons | 0.72 tons
2.21
2.97
2.57
2.41
2.29
2.33
2.51
2.69
2.3
2.91
2.43
2.74
2.32
2.43
2.46
2.77
2.22
2.25
2.78
3.29
2.43
2.79
2.55
3.1
2.31
2.54
3.71
2.51
2.9
Carry out a one-way ANOVA, and test at a 5% level of significance whether any of the pre-load condition variants are
associated with differences in strength. State and explain your conclusion. Explain how you reached your conclusion.
Compute and report the p-value of your observed statistic.
Carry out a multiple-comparison analysis to determine which, if any, of the four pre-load conditions are significantly
different from each other in their resulting strength.
What assumptions are necessary for the ANOVA to be valid? Do these assumptions seem to be satisfied by this particular
set of data? Explain your answer.

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