Question Papers

quantitative techniques

Previous year question paper with solutions for Quantitative techniques from 2007 to 2020

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Syllabus QT (MBA 1st)

Unit-I

Introduction to statistics: meaning, scope, importance and limitations, applications of

inferential statistics in managerial decision-making. Analysis of data: source of data,

collection, classification, tabulation, depiction of data. Measures of Central tendency:

Arithmetic, weighted, geometric mean, median and mode. Measures of Dispersion: Range,

Quartile deviation, Mean deviation, Standard deviation Coefficient of variation, Skewness

and Kurtosis.

Unit-II

Sampling and Sampling Distribution: Concept and definitions, census and sampling,

probability samples and non-probability samples, relationship between sample size and

errors, simple numerical only. Hypothesis Testing: Sampling theory; Formulation of

Hypotheses; Application of Z-test, t-test, F-test and Chi-Square test, techniques of association

of attributes & testing. Test of significance for small sample

Unit-III

Correlation Analysis: Significance, types, Methods of correlation analysis: Scatter diagrams,

Graphic method, Karl Pearson‟s correlation co-efficient, Rank correlation coefficient,

Properties of Correlation. Regression analysis: meaning, application of regression analysis,

difference between correlation & regression analysis, regression equations, standard error and

Regression coefficients. Index Number: Definition, and methods of construction, tests of

consistency, base shifting, splicing and deflation, problems in construction and importance of

index number.

Unit-IV

Time Series Analysis: Meaning, Components and various methods of time series analysis

Trend analysis: Least Square method - Linear and Non- Linear equations, Applications in 

business decision-making. Theory of Probability: Definition, basic concepts, events and

experiments, random variables, expected value, types of probability, classical approach,

relative frequency and subjective approach to probability, theorems of probability, addition,

Multiplication and Bays Theorem and its application. Theoretical Distributions: Difference

between frequency and probability distributions, Binomial, Poisson and normal distribution

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