Making Grouped Frequency Distribution

AtiqRehman15 947 views 12 slides Jan 30, 2015
Slide 1
Slide 1 of 12
Slide 1
1
Slide 2
2
Slide 3
3
Slide 4
4
Slide 5
5
Slide 6
6
Slide 7
7
Slide 8
8
Slide 9
9
Slide 10
10
Slide 11
11
Slide 12
12

About This Presentation

Concept about No of observations, Maximum and minimum value,
Frequency distribution and cumulative Frequency distribution
Determine the range of variation
Class width determination
Location of class limit


Slide Content

Course Title: Business Statistics
BBA (Hons)
2
nd
Semester
Course Instructor: Atiq ur Rehman Shah
Lecturer, Federal Urdu University of Arts,
Science & Technology, Islamabad
+92-345-5271959
[email protected]

Learning Objective
• Concept about No of observations,
Maximum and minimum value,
• Frequency distribution and cumulative
Frequency distribution
• Determine the range of variation
• Class width determination
• Location of class limit

Raw Data: IT Department Graduate Level (MCS)
Maximum
Minimum
Number of observations = 27

Frequency Distribution
•A representation, either in a graphical or
tabular format, which displays the number of
observations within a given interval.
•The intervals must be mutually exclusive.

Steps:
1. Deciding number of classes into which the
data are to be grouped
•This is done with a simple formula.
K = 1 + 3.3Log N
•Where K is Number of classes and N is the
Total Number of observations.

•In this example, the classes were found using
this formula.
K= 1 + 3.3 Log (27)
K= 5.7
•Rounding that off to the next whole number
got the number of classes. Which is 6.
•Therefore Number of Classes = 6

2. Determine the range of variation
•“This is the difference between the largest
and the smallest value in the data.”
4- Largest value
1.85- Smallest value
So, Range= 4 - 1.85
Range = 2.15

3. Class width determination
•Determining the approximate width of the classes can be
done by dividing the Range by Number of Classes.
Range- 2.15, Number of Classes- 6
Class width(Approximate) = 2.15/6
= 0.35
The approximate class width therefore used is 0.35

4. Location of class limit
•The largest value in the data is 4, and therefore that is the upper limit of
the last class in the data. The class width can then be subtracted from
each limit until the minimum value is accommodated in the first class.
The classes are made like this:
4- 0.35 = 3.65
»3.65- Becomes the lower limit
»4- Is the upper limit

•The next class is calculated by:
3.64-0.35= 3.29
»3.64- Upper limit
»3.29- Lower limit
•The next class is calculated by:
3.28-0.35 = 2.93
»3.28- Upper limit
»2.93 Lower limit

•This process is continued until the last class is
made.
2.20-0.35 = 1.85
»2.20- Upper Limit
»1.85- Lower Limit

5. Distributing data into appropriate classes