UGC NET Questions (Paper – 1)

Samanyatodrsta anumana draws on broadly experienced uniformities that may not fit neatly into a strict cause–effect pattern. For instance, we infer motion whenever we see continuous change of place, based on a general understanding that changing position goes with being in motion. The relation is grounded in common experience rather than in a specific causal law. Hence such inferences are called samanyatodrsta.

Option A:
Option A, purvavat, is restricted to cause-to-effect reasoning and cannot cover all uniformities that are not clearly causal, such as certain spatial or kinematic regularities.

Option B:
Option B is correct because samanyatodrsta literally means "known from generality" and is designed to handle inferences from widely observed associations, not only from recognised causal links.

Option C:
Option C, sesavat, is effect-to-cause inference and therefore does not match the non-causal generality highlighted in the example.

Option D:
Option D, anvayavyatireki, classifies inference by its use of positive and negative instances for vyapti, not by the causal or non-causal nature of the relation.

Samanyatodrsta anumana draws on widely observed uniformities that need not be strictly causal, for example inferring that something is moving when its position is constantly changing. The basis is a general correlation between two features rather than a detailed causal analysis. Nyaya reserves this term for such inferences grounded in generic co-existence.

Option A:
Option A, purvavat, is tied specifically to cause-to-effect reasoning and thus does not cover all non-causal uniformities of the kind mentioned.

Option B:
Option B is correct because samanyatodrsta literally means "known from generality" and designates inferences that rely on broad patterns of association rather than on clearly articulated causal sequences.

Option C:
Option C, sesavat, is effect-to-cause inference and presupposes a causal explanation, which is not emphasised in the motion example.

Option D:
Option D, kevalavyatireki, describes a vyapti pattern based solely on negative instances and has nothing to do with the causal or non-causal character of the relation.

Samanyatodrsta anumana relies on general regularities that may not be strictly causal, like the rule that whatever changes its place is moving. From repeated observation of this connection, one infers motion when change of position is seen. The relation is known by common experience rather than explicit cause–effect. Therefore the type of inference in the stem is samanyatodrsta.

Option A:
Option A, purvavat, specifically links causes to later effects and does not cover all non-causal regularities.

Option B:
Option B, sesavat, links effects back to earlier causes and so again does not match the example given.

Option C:
Option C is correct because samanyatodrsta literally means “known from generality” and applies to uniform associations that guide such inferences. It fits the moon-motion illustration.

Option D:
Option D, anvayavyatireki, concerns vyapti established through both positive and negative instances, which is another basis of classification, not this particular non-causal pattern.