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Questions and Answers
Which of the following best defines a sampling distribution in statistics?
Which of the following best defines a sampling distribution in statistics?
- The probability distribution of a given random-sample-based statistic (correct)
- The probability distribution of all the individual sample values
- The probability distribution of a population
- The probability distribution of a sample mean
What does the sampling distribution allow analytical considerations to be based on?
What does the sampling distribution allow analytical considerations to be based on?
- The probability distribution of a sample mean
- The probability distribution of a population
- The probability distribution of a statistic (correct)
- The joint probability distribution of all the individual sample values
In statistics, what is the sampling distribution of a statistic?
In statistics, what is the sampling distribution of a statistic?
- The probability distribution of all the individual sample values
- The probability distribution of a sample mean
- The probability distribution of a population
- The probability distribution of the values that the statistic takes on (correct)
When can the sampling distribution be found theoretically?
When can the sampling distribution be found theoretically?
Why are sampling distributions important in statistics?
Why are sampling distributions important in statistics?
Which of the following best describes the shape of the sampling distribution of the mean in Example 6.1.1?
Which of the following best describes the shape of the sampling distribution of the mean in Example 6.1.1?
What is the probability of obtaining a sample mean of 154 in Example 6.1.1?
What is the probability of obtaining a sample mean of 154 in Example 6.1.1?
What is the probability of obtaining a sample mean less than 158 in Example 6.1.1?
What is the probability of obtaining a sample mean less than 158 in Example 6.1.1?
What is the probability of obtaining a sample mean greater than or equal to 160 in Example 6.1.1?
What is the probability of obtaining a sample mean greater than or equal to 160 in Example 6.1.1?
What does the probability distribution in Example 6.1.1 represent?
What does the probability distribution in Example 6.1.1 represent?
Flashcards
Sampling Distribution
Sampling Distribution
The probability distribution of a given random-sample-based statistic.
Sampling Distribution of a Statistic
Sampling Distribution of a Statistic
The probability distribution of the values that the statistic takes on.
Why Sampling Distributions Matter
Why Sampling Distributions Matter
Analytical considerations are based on the probability distribution of a statistic.
When to find Distribution Theoretically
When to find Distribution Theoretically
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Importance in Statistics
Importance in Statistics
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Probability Distribution
Probability Distribution
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Study Notes
Sampling Distribution
- A sampling distribution is a probability distribution of a statistic obtained through repeated sampling from a population.
- The sampling distribution allows analytical considerations to be based on the behaviour of the statistic in repeated samples.
Characteristics of Sampling Distribution
- The sampling distribution of a statistic is a probability distribution of the possible values of the statistic.
- Theoretically, the sampling distribution can be found using the probability distribution of the underlying population.
Importance of Sampling Distributions
- Sampling distributions are important in statistics because they allow us to make inferences about a population based on a sample.
Shape of Sampling Distribution of the Mean
- The shape of the sampling distribution of the mean is approximately normal, even if the underlying population is not normally distributed.
Example 6.1.1
- The probability distribution in Example 6.1.1 represents the sampling distribution of the sample mean.
- The probability of obtaining a sample mean of 154 is a specific value that can be calculated from the sampling distribution.
- The probability of obtaining a sample mean less than 158 can be calculated from the sampling distribution.
- The probability of obtaining a sample mean greater than or equal to 160 can be calculated from the sampling distribution.
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