R built in dataset
[DOCX File]Lab 2: Manipulating Dataframes
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R offers several built-in dataframes. For this activity we will use the “mtcars” dataset that contains 11 variables and 32 cases representing different models of cars. The goal is to create a new variable for this dataframe that represents the engine displacement per cylinder in cubic inches for each vehicle.
[DOCX File]Multiple Regression in R using LARS
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Multiple R-squared: 0.7486, Adjusted R-squared: 0.7348 F-statistic: 54.5 on 13 and 238 DF, p-value: < 2.2e-16 Regression diagnostics using a variety of functions written by Chris Malone for his senior capstone project while an undergraduate at WSU.
[DOCX File]Lab 5 – External Data: Using SQL
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Make sure the built-in “airquality” dataset is available for use in subsequent commands. It would be wise to reveal the first few records of air quality with head() to make sure that . air quality is available. This will also show you the names of the columns of the air quality dataframe which you will need to …
[DOC File]R notes for BIOL 7083, Community Ecology, Fall 2003
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R makes use of “NA” to indicate a blank or missing value, so before reading in a data set with blanks or missing values, replace each blank or missing value with “NA” (not including the quotes). Note that for many R functions to work properly with a data set with missing values, the argument na.rm=T must be included, e.g.: > mean(x, na ...
[DOCX File]SISG Module 3 - University of Washington
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Introduction to R. Session 5: Over and over. Using the code from the slides, obtain the approximate value of: The expected value of the median of a sample of size 501, from the Exp(1) distribution. The variance of the same random variableIn both cases, compare your …
[DOCX File]RStudio - 03; Enzymology data
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The sample data is a built-in dataset about cars from the 1970's in tabular form, used here as a quick example. We can recognise immediately the code that will be executed by R as marked by {r} and usually referred to as code chuncks. The first chunck is a set-up parameter:
[DOC File]SISG Module 3 - University of Washington
https://info.5y1.org/r-built-in-dataset_1_98da85.html
Introduction to R. Session 7: Fitting models. Using the built-in mtcars dataset: Implement a t-test of the null hypothesis that the average miles per gallon is equal in automatic and manual cars. Check that your output is sensible by plotting a boxplot of the same data.
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