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 |

**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) |

- Option : A
- Explanation :

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59. Match List-I with List-II:

List-I | List-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 |

**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) |

- Option : B
- Explanation :

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- 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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