Chicken diet and weight. In previous chapter, we compared the effects of two types of feed at a time. A better analysis would first consider all feed types at once: casein, horsebean, linseed, meat meal, soybean, and sunflower. The ANOVA output below can be used to test for differences between the average weights of chicks on different diets.
DF | Sum Sq | Mean Sq | F value | Pr(>F) | |
---|---|---|---|---|---|
feed | 5 | 231129.16 | 46225.83 | 15.36 | 0.0000 |
residuals | 65 | 195556.02 | 3008.55 |
Conduct a hypothesis test to determine if these data provide convincing evidence that the average weight of chicks varies across some (or all) groups. Make sure to check relevant conditions. Figures and summary statistics are shown below.
Mean | SD | n | |
---|---|---|---|
casein | 323.58 | 64.43 | 12 |
horsebean | 160.2 | 38.63 | 10 |
linseed | 218.75 | 52.24 | 12 |
meatmeal | 276.91 | 64.9 | 11 |
soybean | 246.43 | 54.13 | 14 |
sunflower | 328.92 | 48.84 | 12 |
What are the hypotheses for this test?
The test statistic for the hypothesis test
is: (please round to two decimal places)
The p-value for the hypothesis test is: (please
round to four decimal places)
Interpret the result of the hypothesis test in the context of the
study:
we have given output of the Anova :
Claim :
determine if these data provide convincing evidence that the average weight of chicks varies across some (or all) groups.
## What are the hypotheses for this test?
Ho: μc = μh = μl = μm = μsoy = μsun
Ha: At least one of the means is different
# The test statistic for the hypothesis test
is:
F = 15.36
# The p-value for the hypothesis test is:
= 0.000
# Interpret the result of the hypothesis test in the context of the study:
Since p < α, we reject the null hypothesis and accept that the average weight of chicks is different for each type of diet
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