R tutorial

Dec 19, 2013Download as PPTX, PDF1 like385 views

R Tutorial provides instructions for basic data management and analysis in R. It covers: 1) Importing and saving data using commands like read.csv and write.table; 2) Controlling and selecting variables using commands like data$V1 and data[c(1:10)]; 3) Recoding variables using logical conditions, such as recoding gender from text to numeric; and 4) Common statistical analyses like single and cross tabulation, plots, t-tests, correlation, and regression.

Basic things to know
? You have to get data(there are two ways)
– data <- read.csv(file.choose())
– data <- read.table(“clipboard”,header=T)
? Notice: this one involves the copy board to restore the
data and there should be header for each variables.

? You have to save data
– write.table(“c:/users/admin/desktop/whatever.csv
”,sep=“,”)
? Sep means the way how data are separated.

Basic data management
? In R you use commands to manage data
– data$V1
? This command will get you to the data and control
variable V1

– data[c(1)]
? This command will get you to the data and control the
first variable.

– data[c(1:10)]
? This command will get you to the data and control the
first to tenth variables.

Recode functions
? When dealing with data, we may need to recode
them from one value to another
– For example, you have a variable named Gender, but
the values are like “male” and “female”. If you want to
do statistical analysis, you may want to recode them
into 0 and 1 so that the computer can actually
recognize it.

? Use the following command
– data$Gender[data$Gender==“male”] <- 0
– data$Gender[data$Gender==“female”] <- 1
? Whatever is inside the [] symbol is the logical conditions.

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R tutorial

1. R Tutorial

2. Basic things to know ? You have to get data(there are two ways) – data <- read.csv(file.choose()) – data <- read.table(“clipboard”,header=T) ? Notice: this one involves the copy board to restore the data and there should be header for each variables. ? You have to save data – write.table(“c:/users/admin/desktop/whatever.csv ”,sep=“,”) ? Sep means the way how data are separated.

3. First, you copy them

4. Second, type those codes

5. Third, you can check the data

6. Basic data management ? In R you use commands to manage data – data$V1 ? This command will get you to the data and control variable V1 – data[c(1)] ? This command will get you to the data and control the first variable. – data[c(1:10)] ? This command will get you to the data and control the first to tenth variables.

7. Recode functions ? When dealing with data, we may need to recode them from one value to another – For example, you have a variable named Gender, but the values are like “male” and “female”. If you want to do statistical analysis, you may want to recode them into 0 and 1 so that the computer can actually recognize it. ? Use the following command – data$Gender[data$Gender==“male”] <- 0 – data$Gender[data$Gender==“female”] <- 1 ? Whatever is inside the [] symbol is the logical conditions.

8. Single tabulation

9. Cross tabulation(frequency)

10. Cross tabulation(sample mean)

11. Three way tabulation

12. Basic Plot(bar)

13. Compare means (T-Test)

14. Compare paired means (T-Test)

15. Correlation

16. Regression(simple)

17. Regression(multiple)

18. THE END