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# Test: Sampling Theory - 2

## 40 Questions MCQ Test Quantitative Aptitude for CA CPT | Test: Sampling Theory - 2

Description
This mock test of Test: Sampling Theory - 2 for CA Foundation helps you for every CA Foundation entrance exam. This contains 40 Multiple Choice Questions for CA Foundation Test: Sampling Theory - 2 (mcq) to study with solutions a complete question bank. The solved questions answers in this Test: Sampling Theory - 2 quiz give you a good mix of easy questions and tough questions. CA Foundation students definitely take this Test: Sampling Theory - 2 exercise for a better result in the exam. You can find other Test: Sampling Theory - 2 extra questions, long questions & short questions for CA Foundation on EduRev as well by searching above.
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QUESTION: 2

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QUESTION: 3

### Statistical data may be collected by complete enumeration called

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QUESTION: 4

Statistical data may be collected by partial enumeration called

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QUESTION: 5

The primary object of sampling is to obtain —————— information about population with ————— effort.

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QUESTION: 6

A —————— is a complete or whole set of possible measurements/data corresponding to the entire collection of units.

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QUESTION: 7

A —————— is the set of measurement/data that are actually selected in the course of an investigation/enquiry.

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QUESTION: 8

Sampling error is —————— proportional to the square root of the number of items in the sample.

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QUESTION: 9

Two basic Statistical laws concerning a population are

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QUESTION: 10

The —————— the size of the sample more reliable is the result.

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QUESTION: 11

Sampling is the process of obtaining a

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QUESTION: 12

By using sampling methods we have

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QUESTION: 13

Under —————— method selection is often based on certain predetermined criteria.

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QUESTION: 14

——————— sampling is similar to cluster sampling.

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QUESTION: 15

Value of a —————— is different for different samples.

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QUESTION: 16

A statistic is a ——————— variable.

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QUESTION: 17

The distribution of a —————— is called sampling distribution of that ——————.

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QUESTION: 18

A ——————— distribution is a theoretical distribution that expresses the functional relation between each of the distinct values of the sample statistic and the corresponding probability.

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QUESTION: 19

Sampling distribution is a frequency distribution.

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QUESTION: 20

Sampling distribution approaches ——————— distribution when the population distribution is not normal provided the sample size is sufficiently large.

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QUESTION: 21

The Standard deviation of the ————————— distribution is called standard error.

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QUESTION: 22

The difference of the actual value and the expected value using a model is

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QUESTION: 23

The measure of divergence is ——————— as the size of the sample approaches that of the population.

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QUESTION: 24

The distribution of sample —————— being normally or approximately normally distributed about the population.

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QUESTION: 25

The standard error of the —————— is the standard deviation of sample means.

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QUESTION: 26

There are ————— types of estimates about a population parameter.

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QUESTION: 27

To estimate an unknown population parameter

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QUESTION: 28

When we have an idea of the error that might be involved, we use

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QUESTION: 29

The estimate which is used in making estimation of a population parameter is

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QUESTION: 30

A —————— estimate is a single number.

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QUESTION: 31

A range of values is

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QUESTION: 32

If we do not have any knowledge of population variance, then we have to estimate it from the

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QUESTION: 33

The sample standard deviation may be a good estimate for population standard deviation in case of ——————— samples.

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QUESTION: 34

The sample standard deviation is a biased estimator of population standard deviation in case of —————— samples.

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QUESTION: 35

If the expected value of the estimator is the value of the parameter of estimation then a good estimator shall be

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QUESTION: 36

The difference between sample S.D and the estimate of population S.D is negligible if the sample size is

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QUESTION: 37

Finite population multiplier is

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QUESTION: 38

Sampling fraction is

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QUESTION: 39

The standard error of the mean for finite population is very close to the standard error of the mean for infinite population when the sampling fraction is

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QUESTION: 40

The finite population multiplier is ignored when the sampling fraction is

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