Page 397 - DECO401_MICROECONOMIC_THEORY_ENGLISH

Microeconomic Theory

Notes

Uncertainty is a basic fact of human life.

Probability

The probability of an incident is the ratio of its occurrence (the frequency). It is the ratio of favourable
incidents and total number of incidents. Suppose that there is a situation in which any one out of expected
results. For example, when a dice is thrown then any one number may be 1, 2, 3, 4, 5 and 6.
For indication,
Number of times incident has occurred

Probability = ___________________________________
Total number of possible incidents
Because turning the dice, it gives possible results 1, 2, 3, 4, 5 and 6, in which the related frequency is
1/6 = 0.167 of any number result that is the probability of every result.
In a special situation, if the all possible results are indexed for incident and the every result is distributed
to the probability of incident. Then this is called the probability distribution.
For example, if a coin is tossed and the head is probable to come 0.6 and not to come 0.4, then this shows
the total number of probabilities on the incident, if its occurrence or not occurrence is 1 = (0.6 + 0.4).
The index of every result of an incident and its probability is the probability distribution in the form of
a table which is shown below—

Table 1

Event Toss of Coin Probability of Occurrence
The state of coming “top” 0.6

The state of not coming “top” 0.4
1.0
The probable distribution value is necessarily 0 to 1. If the probability is P , then 0 ≤ P ≤ 1, where i = 1,
i
i
2, … , n.

Where there is risk, there is uncertainty.

Expected Value
There are such statically measures for the probability distribution which mainly are available for the
brief knowledge about the distribution. One of these is used the probable distribution, expected value
or mean average, is the full average of the related value from the several results.
If two possible results are value of X and X and the probability is only P and P of every result then
2
1
2
1
the formula of expected value is
∑ = P (X ) + P (X )
v
1
2
2
1
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