Q. If the mean of population is 25 then the mean of sampling distribution is

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Q. If the population parameter μ and the unbiased estimate of population is x̅ then the sampling error is as

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Q. The theorem which states that as the sample size increases the sampling distribution must approach the normal distribution is classified as

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Q. The conditions such as large sample size to represent population and samples must be drawn randomly are included in

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Q. The measures in sampling that are results of sample analyses are called

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Q. All the values in sample distribution that can freely varies in the selected random sample from population are indicated as

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Q. IF the population standard deviation is not known then the formula used to calculate standard error is as

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Q. If the value of x-bar is 70 and the μ of sampling distribution is 15 with the standard deviation is 20 then the standard normal variable is

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Q. The uncertainty of elements can be reduced with the estimation of

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Q. The procedure of selecting the desired portion from population which describes the characteristics of whole population is

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Q. The standard deviation of a sampling distribution is also classified as

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Q. In sampling distribution, the formula of calculating standard deviation of sample proportion is as

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Q. In stratified sampling, the sample drawn randomly from the strata is classified as

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Q. The difference between corresponding population and unbiased estimate in the terms of absolute value is classified as

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Q. The important principles to determine the valid statistical inference must includes

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Q. The distribution which consists of all the values of sample statistic of sampling is classified as

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Q. The distribution of difference of proportions approximate the normal standard distribution only if

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Q. When the statistical inference is made on the basis of sample results about the characteristics of population then this is classified as

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Q. The type of sampling in which the desired and useful information is gathered from the best position holder is classified as

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Q. The type of sampling In which each element of population has equally likely chance of occurrence in a random sample is classified as

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