It then reads in and displays the table as it should. finally read in the table, remembering to use the quotation marks Multiple R-Squared: Percent of the variance. used setwd in two steps (it was being balky when I tried to set the path otherwise) and checked it after each step. Summary: Residual Standard Error: Essentially standard deviation of residuals / errors of your regression model. made a file under “Users” and called “Rfiles” and in that file made “DataFiles” and moved the text file there. Note, if you “make plain” before the first save, you do get many plain text unicode file saving options…but not knowing what to use, I took the long way around, and let the machine decide.ĥ. re-opened, highlighted and used the “make plain text” command (doodle-shift-T, or under “format”). txt manually, clicking the “OK” on the warning.Ĥ. saved as RTF (the current most basic option, there is no longer a. opened textedit, pasted the table into textedit.Ģ.
#R STUDIO SUMMARY MAC#
Got it to work, but not trivial on a mac if not using a terminal here are the steps I used.ġ.
David holds a doctorate in applied statistics. His company, Sigma Statistics and Research Limited, provides both on-line instruction and face-to-face workshops on R, and coding services in R. Table4 <- aggregate(MASS, list(GENDER, SMOKE, TREATMENT),FUN=max)Ībout the Author: David Lillis has taught R to many researchers and statisticians. Table3 <- aggregate(MASS, list(GENDER, TREATMENT),FUN=mean)įinally, let’s look at maximum body mass across the levels of gender, smoker and treatment. The aggregate command allows us to create more complex tables, across the levels of several categorical variables. Table2 <- aggregate(MASS, list(SMOKE), FUN=mean) Summary A very useful multipurpose function in R is summary (X), where X can be one of any number of objects, including datasets, variables, and linear models, just to name a few. Anyway – now we use the aggregate command to obtain a table of mean body mass across the two levels of smoker (i.e. Graphs created with the plotly R package are. Note that the aggregate command does not return the variable names. Simply printing the plot object will render the chart locally in your web browser or in the RStudio viewer. Table1 <- aggregate(MASS, list(GENDER), FUN=mean) Finally, the function you wish to apply (in this case you want the mean) becomes the third argument. Then the categorical variable appears inside the list command. The continuous variable becomes the first argument. Let’s use the aggregate command to obtain a table of mean body mass across the two levels of gender. GENDER TREATMENT MASS SMOKE EXERCISE RECOVER Cut and paste the following data set into R. We have data on their gender, their body mass in kg, whether or not they exercise, whether or not they smoke, and whether or not they recovered after treatment. Here is a data set of patients receiving medical treatment (A, B or C). This is where the aggregate command is so helpful. In any case, you may wish to produce summary statistics for each level of the categorical variable. Your data set may include other categorical variables such as Ethnicity, Hair Colour, the Treatments received by patients in a medical study, or the number of cylinders in motor vehicles. You may have a complex data set that includes categorical variables of several levels, and you may wish to create summary tables for each level of the categorical variable.įor example, your data set may include the variable Gender, a two-level categorical variable with levels Male and Female. Summary() is widely used to check statistics analysis results: Levels: Northeast South North Central West North Central South South West Northeast West Northeast South North Central North Central West North Central West Northeast Northeast Northeast North Central North Central South North Central North Central South South Northeast South West West North Central North Central North Central Maxsum: interger, indicating how many levels should be shown for factorsĭigits: integer, used for number formatting with signif() (for fault) or format() (for ) The function invokes particular methods which depend on the class of the first argument. Summary() function is a generic function used to produce result summaries of the results of various model fitting functions.
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