STATISTICAL TECHNIQUES AND TOOLS
SAMPLING DISTRIBUTION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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It becomes narrower and less normal
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It becomes narrower and more normal.
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It becomes wider and more normal
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It becomes wider and less normal.
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Detailed explanation-1: -In other words, as the sample size increases, the variability of sampling distribution decreases. Also, as the sample size increases the shape of the sampling distribution becomes more similar to a normal distribution regardless of the shape of the population.
Detailed explanation-2: -As explained above, the shape of the t-distribution is affected by sample size. As the sample size grows, the t-distribution gets closer and closer to a normal distribution. Theoretically, the t-distribution only becomes perfectly normal when the sample size reaches the population size.
Detailed explanation-3: -Sampling distributions of means get closer to normality as the sample size increases. Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.