Statistics324_HW1 - Statistics 324 Discussion 311 w Jack...

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Statistics 324 – Discussion 311 w/ Jack Homework 1 - Victoria Yakovleva The hellung data frame has 51 rows and 3 columns. Diameter and concentration of Tetrahymena cells, with and without glucose added to growth medium. This data frame contains the following columns: glucose a numeric vector code 1: yes, 2: no. conc a numeric vector. Cell concentration (counts/ml) diameter a numeric vector. Cell diameter ($μ$m) 1. summary(hellung) glucose conc diameter Min.:1.000 Min.: 11000 Min.:19.20 1st Qu.:1.000 1st Qu.: 27500 1st Qu.:21.40 Median:1.000 Median : 69000 Median :23.30 Mean:1.373 Mean:164325 Mean:23.00 3rd Qu.:2.000 3rd Qu.:243000 3rd Qu.:24.35 Max.:2.000 Max.:631000 Max.:26.30 hellung$glucose <- factor(hellung$glucose, labels = c("Y", "N")) summary(hellung) glucose conc diameter Y:32 Min.: 11000 Min.:19.20 N:19 1st Qu.: 27500 1st Qu.:21.40 Median: 69000 Median:23.30 Mean:164325 Mean:23.00 3rd Qu.:243000 3rd Qu.:24.35 Max.:631000 Max.:26.30 The second summary is more informative because it indicates how many of cell colonies have glucose added to the growth medium and how many don’t. The first summary treated the presence or absence of glucose as a number, therefore calculating the median, mean, etc. by using all the 1’s and 2’s. In this case, glucose is categorical, not numerical, therefore having the number of yes’s and number of no’s is much more informative.
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2. with(hellung, bwplot(~conc, xlab= "Cell concentration (counts/ml)", main = "Concentration of Cell Colonies"))
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Statistics324_HW1 - Statistics 324 Discussion 311 w Jack...

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