Sampling methods, distributions, estimation - One Line Questions

1. A confidence level of 90% typically uses a critical Z-value of approximately: — 1.645
2. A point estimate is: — A single value that is the best guess for the population parameter.
3. A confidence interval provides: — A range of values that is likely to contain the population parameter, with a certain level of confidence.
4. For a given confidence level, a larger sample size results in: — A narrower confidence interval.
5. Which of the following best describes a consistent estimator? — An estimator whose variance approaches zero as the sample size increases.
6. In Simple Random Sampling, each member of the population has: — An equal and known chance of being selected.
7. Which of the following is a property of a good estimator? — Efficiency
8. Which sampling technique is characterized by dividing the population into homogeneous subgroups (strata) and then randomly sampling from each stratum? — Stratified Random Sampling
9. Which sampling method involves selecting every k-th element from a list? — Systematic Sampling
10. The margin of error in a confidence interval is calculated as: — Critical value × Standard Error
11. Degrees of freedom for a t-distribution when estimating a population mean are typically: — Equal to n-1.
12. Which of the following is a key concept in estimation? — Determining a population parameter based on sample statistics
13. As the sample size increases, the standard error of the mean: — Decreases
14. In a two-stage sampling process, the first stage typically involves sampling: — Clusters or primary units.
15. Which of the following is a characteristic of the t-distribution compared to the Z-distribution? — It has heavier tails and is flatter at the peak.
16. What is the main advantage of Stratified Random Sampling? — It ensures representation of all subgroups within the population.
17. What is the primary limitation of purposive sampling? — It is subject to researcher bias and lacks generalizability.
18. An unbiased estimator is one where: — The expected value of the estimator equals the population parameter.
19. Convenience sampling is also known as: — Accidental sampling
20. If a researcher wants to be 99% confident that their interval estimate contains the population mean, compared to a 95% confidence interval, the interval will be: — Wider.
21. The standard deviation of the sampling distribution of the sample mean is called the: — Standard error of the mean
22. Quota sampling is a type of: — Non-probability sampling.
23. Which factor, when increased, leads to a wider confidence interval? — Confidence level
24. A researcher wants to study the opinions of students in different faculties of a university. They decide to randomly select a proportional number of students from each faculty. This is an example of: — Stratified Random Sampling
25. Which of the following is a non-probability sampling technique? — Convenience Sampling
26. Which sampling method is prone to selection bias if the list used is incomplete or outdated? — Systematic Sampling
27. In multi-stage sampling, the population is divided into stages, and sampling occurs at each stage. This method is often used for: — Geographically dispersed populations.
28. Which sampling method relies on the researcher's judgment to select participants? — Purposive Sampling
29. Which sampling method is used when the population is too large to sample from directly, and is divided into groups, with some groups selected entirely for study? — Cluster Sampling
30. Which of the following is NOT a probability sampling method? — Quota Sampling
31. If the population standard deviation (σ) is known and the sample size (n) is large, which distribution is typically used for inference about the population mean? — Z-distribution
32. When estimating a population proportion, what distribution is typically used for large sample sizes? — Normal distribution (Z-distribution)
33. What is a sampling distribution? — The distribution of a statistic (e.g., sample mean) calculated from all possible samples of a given size from a population.
34. What is a sampling frame? — A list or map from which a sample is drawn.
35. Snowball sampling is particularly useful for researching: — Hard-to-reach or hidden populations.
36. Cluster sampling is most effective when: — The population can be easily divided into natural, homogeneous groupings (clusters).
37. What is the main assumption when using the t-distribution for confidence intervals? — The population is normally distributed.
38. The mean of the sampling distribution of the sample mean is equal to: — The population mean.
39. The sampling distribution of the sample proportion is approximately normal if: — np ≥ 10 and n(1-p) ≥ 10.
40. The standard error of the mean is calculated as σ/√n. What does 'σ' represent? — The population standard deviation.
41. What does the standard error of the mean measure? — The variability of sample means around the population mean.
42. A 95% confidence interval means: — There is a 95% chance that the population parameter falls within the calculated interval.
43. The primary disadvantage of non-probability sampling methods is: — They do not allow for generalization to the population.
44. What is the primary goal of sampling in research? — To select a subset of the population that accurately represents the entire population.
45. What is the main purpose of estimation in statistics? — To make educated guesses about population parameters based on sample data.
46. What is the critical value used for in constructing a confidence interval? — To determine the width of the interval based on the desired confidence level and the sampling distribution.
47. According to the Central Limit Theorem, if the sample size is sufficiently large, the sampling distribution of the sample mean will be: — Approximately normal
48. When is the t-distribution most similar to the Z-distribution? — When the degrees of freedom are high (large sample size).
49. When the population standard deviation is unknown and the sample size is small (n < 30), which distribution is commonly used for inference about the population mean? — t-distribution
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