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To solve this problem, we need to determine how many people should be sampled from each stratum based on a proportional stratified sampling approach. However, the proportions for each age group are not provided in the image.

Typically, to conduct proportional stratified sampling, the researcher must first know the percentage or proportion of the population in each age group (stratum). The total population sampled is 350, so we need to distribute this total number across the different age groups based on their proportion in the population.

Here are the steps we would typically follow to calculate the number of people to sample from each group:

1. **Obtain Proportions**: The proportions of the population in each of the following age groups:
   - Under 18
   - 18–25
   - 26–50
   - 51–65
   - Over 65

2. **Multiply Proportions by Sample Size**: Once the proportions are known, we multiply each proportion by the total sample size (350) to get the number of people sampled from each stratum.

For example, if 20% of the population is in the "Under 18" group, you would sample:
\[
\text{Sample from "Under 18"} = 0.20 \times 350 = 70 \text{ people}
\]

To proceed, you would need to either be provided with these proportions or calculate them based on known data.

Would you like further clarification or help finding these proportions?

Here are 5 questions to expand on this concept:
1. How are population proportions typically calculated for different age strata?
2. What is the significance of using proportional stratified random sampling in research?
3. What would happen if you used equal sampling from each age group rather than proportional sampling?
4. Can you calculate the sampling size for each group with hypothetical percentages?
5. How can sampling bias affect the results of a stratified sampling survey?

**Tip**: In stratified sampling, the accuracy of your representation of the population depends heavily on the accuracy of the proportions used for the strata.

A researcher is conducting proportionate stratified random sampling with a sample size of 350. Approximately how many people should he sample from each stratum?

Learn how to calculate the sample size for each stratum in proportionate stratified random sampling with a total sample size of 350. Understand the mathematical concepts of proportional stratified sampling, population proportions, and how to apply the relevant formulas.

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