# Lecture 2 – Grouped Data Calculation

Document Sample

```					Lecture 2 – Grouped Data Calculation
Mean, Median and Mode 2. First Quantile, third Quantile and Interquantile Range.
1.

Mean – Grouped Data
Example: The following table gives the frequency distribution of the number of orders received each day during the past 50 days at the office of a mail-order company. Calculate the mean. Number f of order 10 – 12 13 – 15 16 – 18 19 – 21 Solution: Number of order 10 – 12 13 – 15 16 – 18 19 – 21 f 4 12 20 14 n = 50 x 11 14 17 20 fx 44 168 340 280 = 832 X is the midpoint of the class. It is adding the class limits and divide by 2. 4 12 20 14 n = 50

x=

 fx = 832 =16.64
n 50

Median and Interquartile Range – Grouped Data
Step 1: Construct the cumulative frequency distribution. Step 2: Decide the class that contain the median. Class Median is the first class with the value of cumulative frequency equal at least n/2. Step 3: Find the median by using the following formula:
Median = Lm  n  2 -F +  fm    i  

Where: n = the total frequency F = the cumulative frequency before class median f = the frequency of the class median
m

i = the class width Lm = the lower boundary of the class median

Example: Based on the grouped data below, find the median: Time to travel to work 1 – 10 11 – 20 21 – 30 31 – 40 41 – 50 Solution: 1st Step: Construct the cumulative frequency distribution Time to travel to work 1 – 10 11 – 20 21 – 30 31 – 40 41 – 50 Frequency 8 14 12 9 7 Cumulative Frequency 8 22 34 43 50 Frequency 8 14 12 9 7

So,

n 50   25 2 2 F = 22, fm = 12,

class median is the 3rd class

Lm = 20.5 and i = 10

Therefore,
n  -F   Median = Lm   2 i fm      25 - 22  = 21.5   10  12  = 24

Thus, 25 persons take less than 24 minutes to travel to work and another 25 persons take more than 24 minutes to travel to work.

Quartiles
Using the same method of calculation as in the Median, we can get Q1 and Q3 equation as follows:
n  4-F Q1  LQ1 +   fQ1    i  
 3n  4 -F Q3  LQ3 +   f Q3    i  

Example: Based on the grouped data below, find the Interquartile Range

Time to travel to work 1 – 10 11 – 20 21 – 30 31 – 40 41 – 50

Frequency 8 14 12 9 7

Solution: 1st Step: Construct the cumulative frequency distribution Time to travel Frequency to work 1 – 10 8 11 – 20 14 21 – 30 12 31 – 40 9 41 – 50 7 2nd Step: Determine the Q1 and Q3 Cumulative Frequency 8 22 34 43 50

Class Q1 

n 50   12.5 4 4 Class Q1 is the 2nd class Therefore,

n  -F   Q1  LQ1   4 i  fQ1     12.5 - 8   10.5   10 14    13.7143

3n 3  50  Class Q3    37.5 4 4

Class Q3 is the 4th class Therefore,

n  -F   Q3  LQ3   4 i fQ3      37.5 - 34   30.5   10 9    34.3889

Interquartile Range
IQR = Q3 – Q1

IQR = Q3 – Q1 calculate the IQ IQR = Q3 – Q1 = 34.3889 – 13.7143 = 20.6746

Mode – Grouped Data
Mode
•Mode is the value that has the highest frequency in a data set. •For grouped data, class mode (or, modal class) is the class with the highest frequency. •To find mode for grouped data, use the following formula:
  Δ1 Mode = Lmo +  i Δ1 + Δ2  

Where: i is the class width
1 is the difference between the frequency of class mode and the frequency

of the class after the class mode
2 is the difference between the frequency of class mode

and the frequency of the class before the class mode
Lmo is the lower boundary of class mode

Calculation of Grouped Data - Mode
Example: Based on the grouped data below, find the mode

Time to travel to work
1 – 10 11 – 20 21 – 30 31 – 40 41 – 50 Solution: Based on the table,

Frequency
8 14 12 9 7

Lmo = 10.5, 1 = (14 – 8) = 6, 2 = (14 – 12) = 2 and

i = 10
 6  Mode = 10.5   10  17.5 62 

Mode can also be obtained from a histogram. Step 1: Identify the modal class and the bar representing it Step 2: Draw two cross lines as shown in the diagram. Step 3: Drop a perpendicular from the intersection of the two lines until it touch the horizontal axis. Step 4: Read the mode from the horizontal axis

Variance and Standard Deviation -Grouped Data
Population Variance:
2 

 fx

2

  fx  
N N
2

2

Variance for sample data: Standard Deviation: Population: Sample:

s 
2

 fx



  fx 
n

2

n 1

2  2

s2  s2

Example: Find the variance and standard deviation for the following data:

No. of order 10 – 12 13 – 15 16 – 18 19 – 21 Total Solution: No. of order 10 – 12 13 – 15 16 – 18 19 – 21 Total f 4 12 20 14 n = 50 x 11 14 17 20 fx 44 168 340 280 832

f 4 12 20 14 n = 50

fx2 484 2352 5780 5600 14216

Variance,

s2 

 fx

2

  fx  
n 1 n
2

2

50 50  1  7.5820 

 832  14216 

2 Standard Deviation, s  s  7.5820  2.75

Thus, the standard deviation of the number of orders received at the office of this mail-order company during the past 50 days is 2.75.

```
DOCUMENT INFO
Shared By:
Categories:
Stats:
 views: 7360 posted: 11/24/2009 language: English pages: 14
Lingjuan Ma MS
About work for China Compulsory Certification. Some of the documents come from Internet, if you hold the copyright please contact me by huangcaijin@sohu.com