- Distinguish between decision making under certainty and decision making under uncertainty. Mention certain methods for solving decision problems under uncertainty. Discuss how these methods can be applied to solve decision problems.
- Distinguish between probability and non-probability sampling. Elucidate the reasons for the use of non-probability sampling in many situations in spite of its theoretical weaknesses.
- What are models? Discuss the role of models in decision-making. How can you classify models on the basis of behavior characteristics?
- What are matrices? How are determinants different from matrices? Discuss few applications of matrices in business.
Write short notes on any ten of the following:
(a) Concept of Maxima and Minima
(b) Types of classification of data
(c) Pascal Distribution
(d) Multistage sampling & Multiphase sampling
Models for Time Series
(f) Determinant of a Square Matrix
(g) Primary and Secondary Data
(h) Bernoulli Process
(i) The Student’s t Distribution
(j) Use of Autocorrelations in identifying Time Series
(K) Absolute value function
(m) Criteria of pessimism in decision theory
(n) Cluster vs. Stratum
(o) Moving average models
(p) Step function
(q) More than type ogive
(r) Subjectivist’s criterion in decision making
(s) Double sampling
(t) Auto regressive models