Induction is based on observation of facts and is about the world of facts. It has an inductive leap and it is probable in nature.

There are three basic forms of induction such as scientific induction, induction per simple enumeration(or unscientific induction) and analogy.

Scientific induction:

In scientific induction the conclusion seeks to establish a general real proposition. It is based on observation or experiment of facts.

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It involve an inductive leap.

It is probable in nature.

Induction per Simple Enumeration:

Its main characteristics are

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a) It is based on uncontradictory experience

b) It establishes a general real proposition

c) It has an inductive leap

d) It does not rely on the law of causation ANALOGY:

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Analogy is a kind of probable inference from one particular to another particular based on their resemblance. Its main characteristics are

a) It is based on observation of facts

b) It has inductive leap

c) It is probable

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The strength of an analogy depends on the number and importance of the points of resemblance of the particulars.

On the basis of this an analogy may be good or bad.

Probability:

Inductive generalizations are probable. Mathematical probability is different from the probablity used in science.

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Sometimes the idea of probability is explained by mathematical ratio. Probability cannot be estimated on the basis of belief. While calculating the probability of complex events, all possible alternatives are considered. There are two theories of probability such as the frequency theory of probability and the reasonableness theory of probability.

An unexpected occurrence of a phenomenon is termed as chance.

Probability is evidence-supporting but chance is not.

FAIR SAMPLE :

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A fair sample is the representative individual of a homogeneous class having all the

defining characteristics of that class. So any one instance is as good as another belonging to the

same class.

A scientific generalization is not an isolated theory rather part of a coherent system in which theories mutually support one another.

Statistical Syllogism :

In a statistical syllogism the conclusion does not necessarily follow from the pre­mises. It is inductive rather than deductive

One premise here is a statistical generalization. The conclusion is probable. The probability of the conclusion depends upon the strength of the attributive class.