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Description:

These data are derived from the bivariate data listed in QELP Data Set #001 (#DATASET-1631). Please go view that dataset to learn about butter clam habitat and life cycle, and how the sample was collected. We feature the univariate length/width ratio data at this web page to exhibit how students and educators might transform data sets at the QELP website into other meaningful data collections.

We see that the distribution of the length/width ratios of butter clams is centered around the mean of 1.28, with one obvious outlier with a value of 1.67. How many standard deviations above the mean does this clam lie?

Students might also test the normality of the data by making a normal quantile or probability plot. A normal quantile plot displays (x, y) data, where x is the the actual data value, and y is the z-score of the quantile of x. A normal quantile plot that is linear indicates that the original data are normally distributed. You can quickly create a normal quantile plot by launching Webstat (click on the orange Play Now button above) and then selecting Graphics>QQ plot.

Students might also consider these questions relating to the physical meaning of the length/width ratio: What shape does an "average" clam have? What about the shape of the outlier clam mentioned above? Does the length/width ratio change as the size of the clam changes? How can the length/width ratio be visualized in the plot of #DATASET-1631? What are the units of measure of the length/width ratio?

Variables:

ratio- length/width ratio

Link To Google Sheets:

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References/Notes/Attributions:

Langkamp, G. and Hull, J., 2022. QELP Data Set 002. [online] Seattlecentral.edu. Available at: <https://seattlecentral.edu/qelp/sets/002/002.html> [Accessed 27 July 2022]

 

R Dataset Upload:

Use the following R code to directly access this dataset in R.

d <- read.csv("https://www.key2stats.com/Puget_Sound_Butter_Clams_Length_Width_Ratios_1670.csv")

R Coding Interface:


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