In a bumper test, three types of autos were deliberately crashed into a barrier at 5 mph, and the resulting damage (in dollars) was estimated. Five test vehicles of each type were crashed, with the results shown below. Research question: Are the mean crash damages the same for these three vehicles?
Crash Damage ($) | ||
Goliath | Varmint | Weasel |
1,600 | 1,290 | 1,090 |
760 | 1,400 | 2,100 |
880 | 1,390 | 1,830 |
1,950 | 1,850 | 1,250 |
1,220 | 950 | 1,920 |
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One-Factor ANOVA | |||||
Source | SS | df | MS | F | p-value |
Treatment | |||||
Error | |||||
Total | |||||
Based on the given hypotheses, choose the right option.
H_{0}: μ_{1} = μ_{2}
= μ_{3}
H_{1}: Not all the means are equal
α = .05
Reject the null hypothesis if p-value < 0.05
Reject the null hypothesis if p-value > 0.05
On the basis of the above findings, we cannot reject the null
hypothesis.
True
False
using data >data analysis>one way ANOVA
we have
Anova: Single Factor | ||||||
SUMMARY | ||||||
Groups | Count | Sum | Average | Variance | ||
Goliath | 5 | 6410 | 1282 | 246320 | ||
Varmint | 5 | 6880 | 1376 | 103580 | ||
Weasel | 5 | 8190 | 1638 | 195170 | ||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Between Groups | 340360 | 2 | 170180 | 0.93665 | 0.418802 | 3.885294 |
Within Groups | 2180280 | 12 | 181690 | |||
Total | 2520640 | 14 |
a )
One-Factor ANOVA | |||||
Source | SS | df | MS | F | p-value |
Treatment | 340360 | 2 | 170180 | 0.9367 | 0.4188 |
Error | 2180280 | 12 | 181690 | ||
Total | 2520640 | 14 | |||
Based on the given hypotheses, choose the right option.
H0: μ1 = μ2 = μ3
H1: Not all the means are equal
α = .05
Reject the null hypothesis if p-value < 0.05
On the basis of the above findings, we cannot reject the null
hypothesis.
True
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