| 模型 | 模型答案 | 正确答案 |
|---|---|---|
| 金声玉亮2.0 | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. |
D |
| deepseekr1 | The researcher is sampling principals from each of the 125 school districts rather than combining all lists. This approach involves dividing the population into distinct groups (districts) and taking a random sample from each group. - **Option A** incorrectly describes this as a simple random sample (SRS). While samples within districts are random, the overall method does not involve selecting from the entire population directly, so it is not SRS. - **Option B** refers to cluster sampling, which would require selecting only a subset of districts (clusters) and sampling within those. Since all districts are included, this is not cluster sampling. - **Option C** mentions systematic sampling, which involves selecting individuals at regular intervals (e.g., every nth person). The question specifies random sampling within districts, so this is irrelevant. - **Option D** correctly identifies the method as **stratified sampling**. By dividing the population into districts (strata) and sampling within each, the researcher ensures representation from all districts. This approach allows for comparative analysis across strata, which a simple random sample might not achieve. **Answer: D** |
D |
| gpto1 | D | D |
| GPT-4o | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. | D |
| llama3.1-70B-Instruct | D |
D |
| llama3.1-405B-Instruct | D. The described procedure is stratified sampling, where the population is divided into subgroups (strata) that are mutually exclusive. Each of the 125 school districts is a stratum. Stratified sampling gives comparative information that a simple random sample wouldn't give. For example, if the researcher wanted to compare the average salary of school principals in District 1 with the average salary of school principals in District 2, the described procedure allows for this comparison. This is not possible with a simple random sample. Therefore, (A) is incorrect. (B) is incorrect because the population was divided into homogeneous groups, not heterogeneous groups. (C) is incorrect because systematic sampling involves selecting samples based on their position in a list, not based on random selection. The best answer is D. |
D |
| DeepSeek-Coder-V2 | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. | D |
| Qwen2-72B-Instruct | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. | D |
| baichuan4 | D | D |
| doubao | D In this case, the researcher is dividing the population (school principals) into strata (the different school districts) and then obtaining a sample from each stratum. This is characteristic of stratified sampling and can provide more detailed and comparative information compared to a simple random sample. It is not a simple random sample as it is specifically sampling from within each district. It is not a cluster sample as the districts are not heterogeneous groups. And it is not systematic sampling. |
D |
| minimax | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. | D |
| kimi | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. Explanation: In this scenario, the researcher is dividing the population of school principals into groups based on the school districts they are part of. Each district is a stratum, and a random sample is taken from each stratum. This is known as stratified sampling. It's a method where the population is divided into subgroups (strata) that share similar characteristics, and then samples are taken from each subgroup. This ensures that each subgroup is represented in the sample, which can provide more reliable comparative information across different subgroups, such as different school districts in this case. |
D |
| wenxinyiyan | D | D |
| zhipu | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. Explanation: The researcher is obtaining a random sample of principals from each of the 125 school districts. This method ensures that each district (stratum) is represented in the sample, which is characteristic of stratified sampling. Stratified sampling can provide more accurate and detailed information compared to a simple random sample, as it ensures representation from all subgroups (districts, in this case). Option A is incorrect because it describes a simple random sample, which is not what is being done here. Option B is incorrect because cluster sampling involves dividing the population into clusters and then randomly selecting entire clusters, not individuals within each cluster. Option C is incorrect because systematic sampling involves selecting every kth individual from a list, which is not the method described. |
D |
| gpto1 | D | D |
| deepseekv3 | D. This is a stratified sample, which may give comparative information that a simple random sample wouldn't give. Explanation: The researcher is dividing the population (school principals) into distinct groups (school districts) and then obtaining a random sample from each group. This is the definition of stratified sampling. Stratified sampling can provide more detailed and comparative information about each subgroup (district) than a simple random sample would, which is why D is the correct answer. |
D |