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In 2017, Bradbury et al. published an article in Animal Production Science, number 57, pages 2016 – 2026, where they analyzed the effects of a highly soluble calcium source supplemented with phytase in chicken diets and studied the digestibility of various nutrients, ash content, mobility of animals and weakness of the legs. The selection of this study for this article is not to compare it with other experiments, but to simply use it as a model on how to analyze and interpret biostatistics in such a publication:
A scientific article should, in addition to informing us of a series of findings made by the authors, be a guide that allows other researchers, following the same (or similar) methods and materials reach (or not) similar conclusions. than the authors thereof.
What should we look for when reading an article?
Bradbury et al. in table 3 of their article, reported the effect of phytase levels between days 1 to 14, using a 2 x 2 x 2 factorial design (two sources of calcium, two levels of calcium and two levels of phytase, see table 1).
The mean is a descriptive statistical parameter of a population.
There are multiple descriptive statistical parameters such as mean, standard deviation, proportion, etc.
At the beginning of the experiment, the authors or ourselves did not know the real data of the weight gain, the consumption and the conversion index of the total chicken population (Cobb-500 in this case).
From the 1120 chickens used in this experiment, we collect the samples, and estimate the value of the statistical parameter of interest, in this case the mean.
Would we always get the same results when testing a sample of 1120 Cobb-500 chickens? Of course not, they can be very similar, but not the same, that is why the value we obtain from a sample is called the estimate of the mean and as such has an associated error.
The value of the statistic (the mean) of the sample is used to estimate the value of the unknown parameter of the population. If the samples are random, the statistics give unbiased point estimates of the corresponding parameters.
However, as a result, the point estimate does not give us enough information about the test.
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