Questions and Answers
What is the central limit theorem?
The mean of the sample would be equal to the mean of the population; should always be larger than or equal to 30 if possible; when the sample size is large, the sampling distribution is approximately normal.
What is the standard deviation of the sampling distribution of x̅ called?
Standard error of the mean
Is the statement true? The mean of the sampling distribution of p-hat is p.
True
What is a point estimate?
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What is the difference between statistical significance and practical significance?
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Study Notes
Central Limit Theorem
- The mean of the sampling distribution of a sample (x̅) equals the population mean.
- For reliable results, sample sizes should ideally be 30 or larger.
- With a large sample size, the sampling distribution approximates a normal distribution.
Standard Error of the Mean
- The standard deviation of the sampling distribution of x̅ is referred to as the standard error of the mean.
Sampling Distribution of p-hat
- The mean of the sampling distribution of p-hat is equal to the actual population proportion (p).
Point Estimate
- A point estimate is a sample statistic used to estimate a specific population parameter.
Statistical vs. Practical Significance
- Statistical Significance: Indicates that a sample statistic is unlikely to have originated from the population defined by the null hypothesis.
- Practical Significance: Concerns whether the difference between the sample statistic and the null hypothesis parameter is meaningful or important in a real-world context.
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Description
Test your knowledge of key concepts from Statistics 202, Chapters 8-10, through these flashcards. Focus on essential terms like the central limit theorem and the standard error of the mean. Perfect for students looking to reinforce their understanding of statistical principles.