UGC NET COMMERCE SOLVED PAPERS 2017-19 - UGC NET COMMERCE June 2019

57. Match List-I with List-II:

List-I (Objectives of business firms)List-II (Hypothesis)
(a) Maximization of firms’ growth rate(i) Baumol’s hypothesis
(b) Managerial utility function(ii) Marris hypothesis
(c) Satisfying behaviour(iii) Williamson hypothesis
(d) Sales Maximization(iv) Cyert March hypothesis
Choose the correct code from those given below:

Codes

 (a)(b)(c)(d)
1(ii)(iii)(iv)(i)
2(iii)(iv)(i)(ii)
3(iv)(i)(ii)(iii)
4(i)(ii)(iii)(iv)

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59. Match List-I with List-II:

List-IList-II
(a) Ind AS-16(i) Income tax
(b) Ind AS-38(ii) Leasing
(c) Ind AS-17(iii) Intangible assets
(d) Ind AS-12 (iv) Property, plant and equipment
Choose the correct code from those given below:

Codes

 (a)(b)(c)(d)
1(iv)(iii)(i)(ii)
2(iv)(iii)(ii)(i)
3(iii)(ii)(iv)(i)
4(iv)(ii)(i)(iii)

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60. Which of the following are considered nonparametric tests?
(a) Mann-Whitney U test
(b) Kruskal-Wallis test
(c) F-test
(d) T-test
(e) Chi-square test
Choose the correct option from the following:

  • Option : A
  • Explanation : Non-parametric tests vs. Parametric tests: Tests appropriate for analyzing ordinal and nominal data are called non-parametric tests. In contrast, tests for analyzing interval or ratio scale are called parametric tests. Parametric tests (z, t or F) require that certain assumption s be valid concerning the population from where the samples were drawn while non-parametric require few assumptions.Tests involving ranks of data are non-parametric. Non-parametric tests are not as powerful as parametric statistics and tend to err on the conservative side.
    Examples of Non-parametric tests:
    Chi-square test: Test of hypothesis to determine if categorical data shows dependency or if two classifications are independent.
    One sample sign test: Test of hypothesis related single value for given data.
    Two sample sign test, Fisher-Irwin test, Rank sum test (Wilcoxon-Mann-Whitney test i.e., U test, Kruskal-Wallis test i.e., H test), Wilcoxon Matched pairs test/Signed Rank test: Test of hypothesis related no difference among two or more sets of data.
    Charles Spearman’s rank correlation, Kendall’s Coefficient of concordance: Test of hypotheses related to relationship between variables.
    Kruskal-Wallis test: Test of hypothesis between more than two sets of data are analogous to ANOVA in parametric test.
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