Information for Decision Making Ch 31
Decision Making
It is choosing one or more then one courses of action among available different / alternative courses
of action.
Strategic Decisions
Strategic decisions concern the general direction and overall policy of a business. They are far reaching and
can influence the performance of the business. They are also called long term decision.
The Decision Making Process
Identifying
Control Review
Objectives
Communication Collecting
& Carry out Information &
Ideas
Analyzing
Decision Making Information &
Ideas
Constraints on Decision Making
Internal Constraints
Availability of finance
Existing company policy
People behavior
External Constraints
Govt. legislation
Competitors behavior
Lack of technology
The economic environment
Factors Which Determine the Reliability of Data
Whether it is secondary or primary data
Sample size
Questionnaires biasness
Inappropriate sampling method
Poor response rate
Interpreting Statistical data
Results of different researches or collected information in the form of data are in ‘Raw’ form. They have not
been ordered, presented or analyzed in any way to aid their interpretation by the user. This raw data needs to
be summarized so that it can be used in decision making.
Basic Statistical Techniques
Averages/ Central Tendency
It is a measure of the most likely or common result from a set of data. It offers the general picture of
the data without comparing one with each of the observation in a short time. Three frequently used
averages are;
Arithmetic mean/ Mean
It is defined as a value obtained by dividing the sum of all the observation by their number. It
is used for making comparisons between sets of data, e.g. attendance at football clubs
Mean = Sum of all the observation
Number of the observation
Mean from a Frequency Data
When the number of observation is very large, the data are organized into frequency form
rather than showing each result individually. (Frequency means that how many times it
occurs)
Formula = Σ f(x)
Σ f
where;
x refers to each individual value
f means frequency
Σ means sum of any thing
Note: When frequency is given in a cumulative form, we need not to take sum of the
frequency. Cumulative means adding each frequency to the total of the preceding
frequency. Example on page 477 table 31.4
Mean from a Grouped Data
When data is given in a range form, we need to find x (individual value) by taking the
mid point. For example, wages from 200 to 250, mid point is 225. Detail of example on
page 477 table 31.5
Mode
Mode means the value that occurs most frequently in a set of data. It is used for ordering stock,
e.g. in shoe store, sale of design “X” size 8 is maximum, need to order more than others. A
data having one mode is called Uni-Modal and having two modes is called Bi-Modal.
Median
It is defined as a value which divides a data set that have been ordered, into two equal parts,
one part comprising of observations greater than and other part smaller than it. It is used to
claim like a Trade Union leader can raise a point that salaries of 50% staff is less than Rs
10000 which should increase.
Median item can be fined by using the formula;
If odd numbers = Number of values + 1
2
If even numbers = Number of values
2
= the item of 1 (n th + n+2 th)
2 2 2
For Group data = L + h (n -c )
f 2
where,
“n” stands for last value of cumulative frequency
“c” stands for upper value of c.f where n/2 exist
“h” stands for height (difference between lower limit and upper limit of group data)
“f” stands for frequency group where n/2 exist
“L” stands for lower limit where n/2 exist
Note: See Uses, Advantages and Disadvantages on page 478 table 31.6
Measures of Dispersion
It is quite possible that two or more sets of data may have the same averages (mean, median or
mode) but their individual observations may differ considerably from the average. Thus value of
central tendency does not adequately describe the data. We therefore need some additional
information concerning with how the data are dispersed about the average. This is done by
measuring the dispersion which means ‘the extent to which the observations in a sample or in a
population vary about their mean’.
The two main measures of dispersion are:
The Range
It is defined as the difference between the largest and the smallest observation in a set of data.
It may be misleading due to extreme cases in both sides, that is largest is very largest as
compare to others and lowest is very lowest as compare to others. For example result of class
is, 95, 70, and 68,50,55,15. One student got extra ordinary highest and one got extra ordinary
lowest. This type of data can be misleading.
Formula: R = Xmax - Xmin
The Inter-Quartile Range
To overcome the problem of Range, inter-quartile range is used. In this measure we ignore the
highest 25% and lowest 25 % results. It is the range of the middle 50% of the values and is
found by subtracting the lower quartile from the upper quartile.
Formula: IQR = Q3 – Q1
Q3= 3n th observation (ascending order)
4
Q1= n th observation
4
Where “n” stands for total number of observations.
