**Missing data**

R represents missing observations through the data value NA

We can detect missing values using is.na

> x <- NA # assign NA to variable x

> is.na (x) # is it missing ?

[1] TRUE

Now try a vector to know if any value is missing?

> x <- c(11, NA, 13)

> is.na (x)

[1] FALSE TRUE FALSE

Example : How to work with missing data

> x <- c(11, NA, 13) # vector

> mean (x) 11 + NA + 13/2

[1] NA

> mean (x, na.rm = TRUE ) # NAs can be removed

[1] 12

11 + 13/2 = 12

The null object, called NULL, is returned by some functions and expressions.

Note that NA and NULL are not the same.

NA is a placeholder for something that exists but is missing.

NULL stands for something that never existed at all.

**Logical Operators and Comparisons**

The following table shows the operations and functions for logical comparisons (True or False)

TRUE and FALSE are reserved words denoting logical constants.

**Logical Operators and Comparisons**

- The
__shorter form__performs element-wise comparisons in almost the same way as arithmetic operators. - The
__longer form__evaluates left to right examining only the first element of each vector. Evaluation proceeds only until the result is determined. - The longer form is appropriate for programming control-flow and typically preferred in if clauses (conditional).

Example

> x <- 5

Is x less than 10 or x is greater than 5 ?

> (x < 10) | | (x > 5) # | | means OR

[1] TRUE

Is x greater than 10 or x is greater than 5 ?

> (x > 10) | | (x > 5)

[1] FALSE

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