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Questions and Answers
What is the key difference between population parameters and sample statistics?
What is the key difference between population parameters and sample statistics?
- Population parameters are unique, while sample statistics vary with different samples. (correct)
- Population parameters measure nonsampling errors, while sample statistics measure sampling errors.
- Population parameters have a range of values, while sample statistics have a single value.
- Population parameters estimate the spread of data, while sample statistics estimate the average.
In the context of statistics, what do nonsampling errors refer to?
In the context of statistics, what do nonsampling errors refer to?
- Errors arising from the difference between sample statistics and population parameters.
- Errors in estimating population parameters.
- Errors occurring due to incorrect sampling methods.
- Errors in the collection and processing of data. (correct)
Why do sampling errors only occur in sample surveys and not in censuses?
Why do sampling errors only occur in sample surveys and not in censuses?
- Sampling errors are minimized in censuses due to rigorous data collection methods.
- Censuses involve the entire population, so there is no need for sampling. (correct)
- Censuses use sampling methods that eliminate sampling errors.
- Censuses rely on sample statistics rather than population parameters.
What is the purpose of using rigorous methods in estimating sample statistics?
What is the purpose of using rigorous methods in estimating sample statistics?
Why do nonsampling errors occur according to the text?
Why do nonsampling errors occur according to the text?
How can nonsampling errors be minimized in statistical surveys?
How can nonsampling errors be minimized in statistical surveys?
What is the relationship between the mean of the sampling distribution of x and the mean of the population?
What is the relationship between the mean of the sampling distribution of x and the mean of the population?
When is the standard deviation of x equal to the standard error of x?
When is the standard deviation of x equal to the standard error of x?
What condition must be met for the sampling distribution of x to be approximately normal?
What condition must be met for the sampling distribution of x to be approximately normal?
In the context of the Central Limit Theorem, what happens if X is not normally distributed?
In the context of the Central Limit Theorem, what happens if X is not normally distributed?
Under what condition does σx = √(σ/n) hold true?
Under what condition does σx = √(σ/n) hold true?
What is the significance of using a threshold of 5% for 'small' sample size in comparison to population size?
What is the significance of using a threshold of 5% for 'small' sample size in comparison to population size?
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