R Dataset / Package HistData / Yeast
| Attachment | Size |
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| dataset-14587.csv | 344 bytes |
| Documentation |
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On this Picostat.com statistics page, you will find information about the Yeast data set which pertains to Student's (1906) Yeast Cell Counts. The Yeast data set is found in the HistData R package. Try to load the Yeast data set in R by issuing the following command at the console data("Yeast"). This may load the data into a variable called Yeast. If R says the Yeast data set is not found, you can try installing the package by issuing this command install.packages("HistData") and then attempt to reload the data with library("HistData") followed by data("Yeast"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Yeast at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Yeast R data set. The size of this file is about 344 bytes. Student's (1906) Yeast Cell CountsDescriptionCounts of the number of yeast cells were made each of 400 regions in a 20 x 20 grid on a microscope slide, comprising a 1 sq. mm. area. This experiment was repeated four times, giving samples A, B, C and D. Student (1906) used these data to investigate the errors in random sampling. He says "there are two sources of error: (a) the drop taken may not be representative of the bulk of the liquid; (b) the distribution of the cells over the area which is examined is never exactly uniform, so that there is an 'error of random sampling.'" The data in the paper are provided in the form of discrete frequency distributions
for the four samples. Each shows the frequency distribution squares containing
a Usagedata(Yeast) data(YeastD.mat) Format
DetailsStudent considers the distribution of a total of Nm particles distributed over N unit areas with an average of m particles per unit area. With uniform mixing, for a given particle, the probability of it falling on any one area is p = 1/N, and not falling on that area is q = 1 - 1/N. He derives the probability distribution of 0, 1, 2, 3, ... particles on a single unit area from the binomial expansion of (p + q)^{mN}. SourceD. J. Hand, F. Daly, D. Lunn, K. McConway and E. Ostrowski (1994). A Handbook of Small Data Sets. London: Chapman \& Hall. The data may be found at: http://www.stat.duke.edu/courses/Spring98/sta113/Data/Hand/yeast.dat References"Student" (1906) On the error of counting with a haemocytometer. Biometrika, 5, 351-360. http://www.medicine.mcgill.ca/epidemiology/hanley/c626/Student_counting.pdf Examplesdata(Yeast)require(lattice) # basic bar charts # TODO: frequencies should start at 0, not 1. barchart(count~freq|sample, data=Yeast, ylab="Number of Cells", xlab="Frequency") barchart(freq~count|sample, data=Yeast, xlab="Number of Cells", ylab="Frequency", horizontal=FALSE, origin=0)# same, using xyplot xyplot(freq~count|sample, data=Yeast, xlab="Number of Cells", ylab="Frequency", horizontal=FALSE, origin=0, type="h", lwd=10) -- Dataset imported from https://www.r-project.org. |
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