Stem and Leaf Display

DESCRIPTION:

Prints a stem-and-leaf display for the given data. The form of the display can be produced automatically, or be controlled by the user.

USAGE:

stem(x, nl=<<see below>>, scale=<<see below>>, twodig=F,  
      fence=2, head=T, depth=F)

REQUIRED ARGUMENTS:

x: numeric vector to be displayed. Missing values ( NAs) are allowed.

OPTIONAL ARGUMENTS:

nl

number of different leaf values on a stem. Allowed values are 2, 5, 10. The default is to determine an appropriate value automatically.

scale

position at which the break occurs between the stem and the leaves, counting to the right from the decimal point; e.g., -1 would break between the tens and the units digit. By default, a suitable position is chosen from the range of the data.

twodig

logical flag: if TRUE, two digits are printed for each observation.

fence

the multiple of the inter-quartile range used to determine outliers. By default, any point further than 2 inter-quartile ranges from the nearest quartile is considered an outlier, and is printed separately from the body of the stem-and-leaf display. If the inter-quartile range is zero, the algorithm performs outlier detection by means of quartiles of the remainder of the data after exclusion of values equal to the median and quartiles.

head

if TRUE, print a heading giving median, quartiles, and counts of data values and NAs.

depth

if TRUE, precede each line with depth and count. The count is the number of data values on a line. The depth is the cumulative sum of the counts to the nearer extreme.

.ne 20

SIDE EFFECTS:

a stem and leaf display of x is printed. Stem and leaf displays are very similar to histograms, but retain more information, and are very easy to produce by hand.

DETAILS:

The number of missing values is stated in the printout if head is TRUE .

A number that is precisely zero is identified by z (or zz if twodig is TRUE). An error occurs if there is only one unique value in the data.

REFERENCES:

Hoaglin, D. C., Mosteller, F. and Tukey, J. W., editors (1983). Understanding Robust and Exploratory Data Analysis. Wiley, New York.

Mosteller, F. and Tukey, J. W. (1977). Data Analysis and Regression. Addison-Wesley, Reading, Mass.

Velleman, P. F. and Hoaglin, D. C. (1981). Applications, Basics, and Computing of Exploratory Data Analysis. Duxbury, Boston.

EXAMPLES:

  stem(lottery.payoff) 
N = 254   Median = 270.25 
Quartiles = 194, 365 
Decimal point is 2 places to the right of the colon 
   0 : 8 
   1 : 000011122233333333333344444 
   1 : 55555566666677777778888888899999999999 
   2 : 0000000111111111111222222233333333444444444 
   2 : 555556666666666777778889999999999999999 
   3 : 000000001111112222333333333444 
   3 : 55555555666667777777888888899999999 
   4 : 0122234 
   4 : 55555678888889 
   5 : 111111134 
   5 : 555667 
   6 : 44 
   6 : 7 
High: 756.0 869.5