Sampling Distributions Assessment Test
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A probability distribution of a statistic obtained through a large number of samples drawn from a specific population is...
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Graph
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Sampling distribution
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Sample
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Table
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About This Quiz
In general, a sampling distribution is a probability distribution of a statistic obtained through a large number of samples drawn from a specific population. Take this assessment test to find out more.
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- 2.
The actual or estimated standard deviation of the error in the process by which it was generated is...
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Open error
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Standard error
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Closed error
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Real value
Correct Answer
A. Standard errorExplanation
The correct answer is "Standard error" because it refers to the standard deviation of the error in the process by which the data was generated. It is a measure of the accuracy of the data, indicating how much the observed values deviate from the true values. A smaller standard error indicates less variability and higher precision in the data.Rate this question:
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- 3.
The statistical information from a sample which will vary as the random sampling is repeated is referred to as...
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Linear
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Nominal
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Sampling variability
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Coefficient
Correct Answer
A. Sampling variabilityExplanation
Sampling variability refers to the natural variation in statistical information that occurs when different random samples are taken from the same population. This variation is expected because each sample will have different individuals or elements, leading to different results. Therefore, sampling variability is the correct answer as it accurately describes the concept of variation in statistical information due to random sampling.Rate this question:
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- 4.
A listing or function showing all the possible values of data and how often they occur is...
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Table
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Distribution
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Arrangement
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Line
Correct Answer
A. DistributionExplanation
A listing or function showing all the possible values of data and how often they occur is called a distribution. In statistics, a distribution provides a summary of the frequency or probability of different outcomes in a dataset. It helps in understanding the pattern, variability, and central tendency of the data. By analyzing the distribution, one can identify the most common values, outliers, and overall characteristics of the dataset.Rate this question:
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- 5.
Randomly choosing a sample of k items from a list S containing n items, where n is either a very large or unknown number is...
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Reservoir sampling
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Rule sampling
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Nomination
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Ordination
Correct Answer
A. Reservoir samplingExplanation
Reservoir sampling is a technique used to randomly select a sample of k items from a list S, where the total number of items in the list is either very large or unknown. It works by maintaining a reservoir of size k and iteratively updating it with items from the list. Each new item encountered has a probability of being included in the reservoir, ensuring a uniform and unbiased selection. This method is particularly useful when it is not feasible to store the entire list in memory or when the list size is unknown.Rate this question:
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- 6.
A statistical tool for constructing sampling distributions is the...
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Permutation test
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Combination test
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T test
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Confidence test
Correct Answer
A. Permutation testExplanation
A permutation test is a statistical tool used for constructing sampling distributions. It involves randomly permuting the observed data to create a null distribution, which represents the distribution of the test statistic under the assumption that the null hypothesis is true. By comparing the observed test statistic to the null distribution, we can assess the likelihood of obtaining the observed result by chance alone. This allows us to make inferences about the population from which the sample was drawn. Therefore, a permutation test is a suitable tool for constructing sampling distributions.Rate this question:
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- 7.
A statistical test used on paired nominal data is the...
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McNemar's test
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Apte test
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F test
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Linear test
Correct Answer
A. McNemar's testExplanation
McNemar's test is a statistical test used specifically for paired nominal data. It is commonly used when analyzing data that involves two related variables, such as before-and-after measurements or matched pairs. The test determines if there is a significant difference in the frequencies of two categories within the paired data. It is a non-parametric test that compares the observed frequencies with the expected frequencies under the null hypothesis, and it is suitable for small sample sizes. Therefore, McNemar's test is the appropriate choice for analyzing paired nominal data.Rate this question:
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- 8.
What is used to test the null hypothesis that the median of a distribution is equal to some value?
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Lean test
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Poll test
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Sign test
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Pill test
Correct Answer
A. Sign testExplanation
The sign test is used to test the null hypothesis that the median of a distribution is equal to some value. In this test, the differences between the observed values and the hypothesized median are replaced by their signs (+ or -) and the number of positive and negative signs are compared. If the number of positive and negative signs is approximately equal, then the null hypothesis is accepted.Rate this question:
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- 9.
Which is a method for testing differences between three or more matched sets of frequencies or proportions?
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T test
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Optimum test
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Cochran's Q test
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D test
Correct Answer
A. Cochran's Q testExplanation
Cochran's Q test is a method used to test differences between three or more matched sets of frequencies or proportions. It is specifically designed for categorical data and is used when the data is non-parametric and the observations are dependent on each other. The test determines whether there is a significant difference between the proportions of a categorical variable across multiple groups. It is a useful tool in various fields such as medicine, social sciences, and market research, where researchers want to compare frequencies or proportions among different groups.Rate this question:
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- 10.
What is used for identification and rejection of outliers?
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A test
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E test
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T test
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Q test
Correct Answer
A. Q testExplanation
The Q test is used for the identification and rejection of outliers. The Q test is a statistical test that compares the difference between a data point and the mean value of a dataset to the range of the dataset. If the difference is greater than a certain critical value, the data point is considered an outlier and can be rejected. This test helps in identifying and removing any data points that are significantly different from the rest of the dataset, which can affect the accuracy and reliability of statistical analysis.Rate this question:
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Current Version
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Mar 20, 2023Quiz Edited by
ProProfs Editorial Team -
Dec 25, 2017Quiz Created by
Cripstwick
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