**Question:** Can missing values be handled on R?

**Answer:** Yes, in R language one can handle missing values. The way of dealing with missing values is different as compared to other statistical softwares such as SPSS, SAS, STATA, EVIEWS etc.

**Question:** What is the representation of missing values in R Language?

**Answer:** In R missing values or data appears as NA. Note that NA is not a string nor a numeric value.

**Question:** Can R user introduce missing value(s) in matrix/ vector?

**Answer:** Yes user of R can create (introduce) missing values in vector/ Matrix. For example,

x <- c(1,2,3,4,NA,6,7,8,9,10)

y <- c(“a”, “b”, “c”, NA, “NA”)

Note that on y vector the fifth value of strong “NA” not a missing value.

**Question:** How one can check that there are missing value in a vector/ Matrix?

**Answer:** To check which values in a matrix/vector recognized as missing value by R language, use the *is.na* function. This function will return a vector of TRUE or FALSE. TRUE indicate that the value at that index is missing while FALSE indicate that the value is not a missing value. For example

> is.na(x) # fifth element will appear as TRUE while all other will be FALSE

> is.na(y) # fourth element will be true while all others as FALSE

Note that “NA” in second vector is not a missing value, therefore *is.na* will return FALSE for this value.

**Question:** In R language, can missing values be used comparisons?

**Answer:** No missing values in R cannot be used in comparisons. NA (missing values) is used for all kinds of missing data. Vector x is numeric and vector y is a character object. So Non-NA values cannot be interpreted as missing values. Write the command, to understand it

x < 0

y == NA

is.na(x) <- which(x–7); x1

**Question:** Provide an example for introducing NA in matrix?

**Answer:** Following command will create a matrix with all of the elements as NA.

matrix(NA, nrow=3, ncol=3)

matrix(c(NA,1,2,3,4,5,6,NA, NA), nrow=3, ncol=3)