# Describing Data: Percentiles

## Presentation on theme: "Describing Data: Percentiles"— Presentation transcript:

Describing Data: Percentiles

LEARNING OBJECTIVES LO1. Compute and understand quartiles, deciles, and percentiles. LO2. Construct and interpret box plots.

Quartiles, Deciles and Percentiles
Learning Objective 2 Compute and understand quartiles, deciles, and percentiles. Quartiles, Deciles and Percentiles The median splits the data into equal sized halves Quartiles split the data into quarters Deciles into tenths And percentiles can be any split of our choosing These measures include quartiles, deciles, a

- 50% 50% - Lowest Data Value Median 50% value Highest Data Value Quartiles 25% 25% 25% 25% Q1 Q2 Q3 Deciles 1/10 10% 10% 10% 10% 10% 10% 10% 10% 10% 10%

Percentile Computation
LO2 Percentile Computation To formalize the computational procedure, let Lp refer to the location of a desired percentile. So if we wanted to find the 33rd percentile we would use L33 and if we wanted the median, the 50th percentile, then L50. The number of observations is n, so if we want to locate the median, its position is at (n + 1)/2, or we could write this as (n + 1)(P/100), where P is the desired percentile.

LO2 Percentiles - Example Listed below are the commissions earned last month by a sample of 15 brokers at Salomon Smith Barney’s Oakland, California, office. \$2,038 \$1,758 \$1,721 \$1,637 \$2,097 \$2,047 \$2,205 \$1,787 \$2,287 \$1,940 \$2,311 \$2,054 \$2,406 \$1,471 \$1,460 Locate the median, the first quartile, and the third quartile for the commissions earned.

Percentiles – Example (cont.)
LO2 Percentiles – Example (cont.) Step 1: Organize the data from lowest to largest value \$1,460 \$1,471 \$1,637 \$1,721 \$1,758 \$1,787 \$1,940 \$2,038 \$2,047 \$2,054 \$2,097 \$2,205 \$2,287 \$2,311 \$2,406

Percentiles – Example (cont.)
LO2 Percentiles – Example (cont.) Step 2: Compute the first and third quartiles. Locate L25 and L75 using: 4-8

Learning Objective 3 Construct and interpret box plots.
A box plot is a graphical display, based on quartiles, that helps us picture a set of data. To construct a box plot, we need only five statistics: the minimum value, Q1(the first quartile), the median, Q3 (the third quartile), and the maximum value.

LO3 Boxplot - Example

LO3 Boxplot Example Step1: Create an appropriate scale along the horizontal axis. Step 2: Draw a box that starts at Q1 (15 minutes) and ends at Q3 (22 minutes). Inside the box we place a vertical line to represent the median (18 minutes). Step 3: Extend horizontal lines from the box out to the minimum value (13 minutes) and the maximum value (30 minutes).

Example: Draw a Box & Whisker for
Sample Data in Ordered Array: (n = 9) Q1 (L25) is in the (9+1)*25/100 = 2.5 position of the ranked data so use the value half way between the 2nd and 3rd values, so Q1 = 12.5 Q1 and Q3 are measures of non-central location Q2 = median, is a measure of central tendency

Quartile Measures Calculating The Quartiles: Example
Sample Data in Ordered Array: (n = 9) Q1 is in the (9+1)*25/100 = 2.5 position of the ranked data, so Q1 = (12+13)/2 = 12.5 Q2 is in the (9+1)*50/100 = 5th position of the ranked data, so Q2 = median = 16 Q3 is in the (9+1)*75/100 = 7.5 position of the ranked data, so Q3 = (18+21)/2 = 19.5 Q1 and Q3 are measures of non-central location Q2 = median, is a measure of central tendency

Quartile Measures- Calculation Rules
When calculating the ranked position use the following rules If the result is a whole number then it is the ranked position to use If the result is a fractional half (e.g. 2.5, 7.5, 8.5, etc.) then average the two corresponding data values. If the result is not a whole number or a fractional half then interpolate between the data points.

Quartile Measures: The Interquartile Range (IQR)
The IQR is Q3 – Q1 and measures the spread in the middle 50% of the data The IQR is a measure of variability that is not influenced by outliers or extreme values Measures like Q1, Q3, and IQR that are not influenced by outliers are called resistant measures

The Interquartile Range
Example: Median (Q2) X X Q1 Q3 maximum minimum 25% % % % Interquartile range = 19.5 – 12.5 = 7

Distribution Shape and The Boxplot
Negatively-Skewed Symmetrical Positively-Skewed Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc..

Interpolation If you found that the first quartile was the 13.75th value then you interpolate like this: Take the 13th and 14th data values Find the difference |14th-15th| Multiply the difference by 0.75 Add the calculated value to the 13th value

Exercises – To Do Page 116 – Q4-21 Q4-23 Q4-25

Stem and Leaf Diagrams 35 23 1 2 3 4 1 2 3 4 6 7 5 8 9 8 6 7 3 5 2 7 7 7 9 8 5 3 7 1 2 1 means 18

Stem and Leaf Diagrams

Raw data The following data were collected on the ages of cyclists involved in road accidents

66 6 62 19 20 15 21 8 63 44 10 26 35 61 13 28 7 52 22 64 11 39 9 17 32 36 37 18 138 16 67 45 55 14 49 23 12 88 46 59 25 42 29 60 50 31 34 Total 92

Ages of cyclists in road accidents
Always include a title Always include a Key Key 6|7 means 67 years