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The problem asks to estimate how many of the next 3000 shoppers will be women, based on the given sample data of male and female shoppers. Let's break it down:

### Data from the table:
- Number of men: 62
- Number of women: 116

### Total number of people in the sample:
\[
62 + 116 = 178
\]

### Proportion of women in the sample:
\[
\frac{116}{178}
\]

To find how many of the next 3000 shoppers will be women, multiply this proportion by 3000:
\[
\left(\frac{116}{178}\right) \times 3000
\]

Now let's calculate this.Based on the sample data, it is estimated that **1,955** of the next 3,000 shoppers will be women.

Do you have any questions or would you like more details on this process? Here are five related questions to expand on this:

1. How would the estimate change if the sample size were larger?
2. What proportion of the shoppers in the sample were men?
3. How could we use this data to estimate future trends over a year?
4. What are some potential sources of bias in the sampling method used?
5. How does rounding affect the accuracy of predictions like this?

**Tip:** When dealing with large populations, small changes in sample proportions can have a significant impact on predictions.

Basado en la muestra, ¿cuántos de los próximos 3000 compradores podemos pronosticar que serán mujeres? Redondear la respuesta al número natural más cercano.

Learn how to estimate the number of female shoppers among the next 3,000, based on a sample where 116 out of 178 shoppers were women. This problem demonstrates key concepts in probability, sampling, and proportions.

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