# Statistics with R for Business Analysts – Mean, Median and Mode

## Statistics with R for Business Analysts – Mean, Median and Mode

Statistical analysis in R is performed by using many in-built functions. Most of these functions are part of the R base package. These functions take R vector as an input along with the arguments and give the result.

The functions we are discussing in this chapter are mean, median and mode.

## Mean

It is calculated by taking the sum of the values and dividing with the number of values in a data series.

The function mean() is used to calculate this in R.

### Syntax

The basic syntax for calculating mean in R is −

```mean(x, trim = 0, na.rm = FALSE, ...)
```

Following is the description of the parameters used −

• x is the input vector.
• trim is used to drop some observations from both end of the sorted vector.
• na.rm is used to remove the missing values from the input vector.

### Example

```# Create a vector.
x <- c(12,7,3,4.2,18,2,54,-21,8,-5)

# Find Mean.
result.mean <- mean(x)
print(result.mean)```

When we execute the above code, it produces the following result −

```[1] 8.22
```

## Applying Trim Option

When trim parameter is supplied, the values in the vector get sorted and then the required numbers of observations are dropped from calculating the mean.

When trim = 0.3, 3 values from each end will be dropped from the calculations to find mean.

In this case the sorted vector is (−21, −5, 2, 3, 4.2, 7, 8, 12, 18, 54) and the values removed from the vector for calculating mean are (−21,−5,2) from left and (12,18,54) from right.

```# Create a vector.
x <- c(12,7,3,4.2,18,2,54,-21,8,-5)

# Find Mean.
result.mean <-  mean(x,trim = 0.3)
print(result.mean)```

When we execute the above code, it produces the following result −

```[1] 5.55
```

## Applying NA Option

If there are missing values, then the mean function returns NA.

To drop the missing values from the calculation use na.rm = TRUE. which means remove the NA values.

```# Create a vector.
x <- c(12,7,3,4.2,18,2,54,-21,8,-5,NA)

# Find mean.
result.mean <-  mean(x)
print(result.mean)

# Find mean dropping NA values.
result.mean <-  mean(x,na.rm = TRUE)
print(result.mean)```

When we execute the above code, it produces the following result −

```[1] NA
[1] 8.22
```

## Median

The middle most value in a data series is called the median. The median() function is used in R to calculate this value.

### Syntax

The basic syntax for calculating median in R is −

```median(x, na.rm = FALSE)
```

Following is the description of the parameters used −

• x is the input vector.
• na.rm is used to remove the missing values from the input vector.

### Example

```# Create the vector.
x <- c(12,7,3,4.2,18,2,54,-21,8,-5)

# Find the median.
median.result <- median(x)
print(median.result)```

When we execute the above code, it produces the following result −

```[1] 5.6
```

## Mode

The mode is the value that has highest number of occurrences in a set of data. Unike mean and median, mode can have both numeric and character data.

R does not have a standard in-built function to calculate mode. So we create a user function to calculate mode of a data set in R. This function takes the vector as input and gives the mode value as output.

### Example

```# Create the function.
getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
}

# Create the vector with numbers.
v <- c(2,1,2,3,1,2,3,4,1,5,5,3,2,3)

# Calculate the mode using the user function.
result <- getmode(v)
print(result)

# Create the vector with characters.
charv <- c("o","it","the","it","it")

# Calculate the mode using the user function.
result <- getmode(charv)
print(result)```

When we execute the above code, it produces the following result −

```[1] 2
[1] "it"```

R tutorials for Business Analyst – How to Replace Missing Values(NA) in R

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