# ISS (Statistical Services) Statistics Paper II (New 2016 MCQ Pattern): Questions 163 - 165 of 253

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## Question number: 163

» Statistical Inference and Hypothesis Testing » Factorization Theorem

### Question

Which of the following definitions of Sufficiency of a estimator is known as Fisher-Neyman Factorization Theorem?

### Choices

Choice (4) | Response | |
---|---|---|

a. | An estimator is said to be sufficient for if it provides all the information contained in the sample about the parametric function | |

b. | If is a estimator of parameter based on a sample of size n from the population with density such that the conditional distribution of given T is independent of then T is sufficient estimator of . | |

c. | A statistic is sufficient estimator of parameter if and only if the likelihood function (joint p. d. f. of the sample) can be expressed as where is the p. d. f. of statistic and is a function of sample observations only independent of | |

d. | Question does not provide sufficient data or is vague |

## Question number: 164

» Statistical Inference and Hypothesis Testing » Factorization Theorem

### Question

Factorization theorem for sufficiency is known as

### Choices

Choice (4) | Response | |
---|---|---|

a. | Fisher-Neyman Theorem | |

b. | Bernoulli Theorem | |

c. | Cramer-Rao Theorem | |

d. | Rao-Blackwell Theorem |

## Question number: 165

» Statistical Inference and Hypothesis Testing » Confidence Interval Estimation

### Question

Suppose there is a survey carried out on 200 persons and the calculated mean and Standard Deviation are 5.83 and 0.86 respectively, then the confidence interval of 95 % of the population mean would be

### Choices

Choice (4) | Response | |
---|---|---|

a. |
| |

b. |
| |

c. |
| |

d. | All of the above |